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Development of a rapid UHPLC method for
the in-process determination of coupling
reagents used in peptide synthesis
Deborah Barry
BSc. Analytical Science
Student number: 53423671
A thesis submitted to Dublin City University for consideration for the degree of:
Master of Science
School of Chemical Sciences
Dublin City University
Supervisors:
Dr. Damian Connolly, Pharmaceutical and Molecular Biotechnology Research Center (PMBRC),
Department of Chemical and Life Sciences, Waterford Institute of Technology
and
Dr. Andreas Heise, School of Chemical Sciences, Dublin City University
July 2013
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I hereby certify that this material, which I now submit for assessment on the programme of study
leading to the award of Master of Science is entirely my own work, that I have exercised reasonable
care to ensure that the work is original, and does not to the best of my knowledge breach any law of
copyright, and has not been taken from the work of others save and to the extent that such work has
been cited and acknowledged within the text of my work.
Signed: ____________________
Student ID No.: ______________
Date: ______________________
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TABLE OF CONTENTS
ABSTRACT ............................................................................................................................................. 6
ABBREVIATIONS ................................................................................................................................. 7
LIST OF FIGURES ............................................................................................................................... 11
LIST OF TABLES ................................................................................................................................. 13
ACKNOWLEDGEMENTS ................................................................................................................... 15
1.1 Overview of peptides and proteins .............................................................................................. 17
1.2 The use of peptides as drug candidates ........................................................................................ 18
1.3 Advances in the use of peptides as drug candidates .................................................................... 19
1.4 Sources of peptides ...................................................................................................................... 20
1.5 Chemical synthesis of peptides .................................................................................................... 21
1.5.1 Liquid phase peptide synthesis (LPPS) ............................................................................... 23
1.5.2 Solid phase peptide synthesis .............................................................................................. 23
1.6 Peptide coupling reagents ............................................................................................................ 25
1.6.3 Oxyma based additives ....................................................................................................... 31
1.6.4 Oxyma based uronium salts ................................................................................................ 31
1.6.5 Immonium reagents ............................................................................................................ 32
1.6.6 Cleavage, deprotection and isolation of the peptide .......................................................... 33
1.7 Analytical evaluation of peptides ................................................................................................ 34
1.7.1 The use of analytical chemistry for the purification and characterisation of peptides ...... 34
1.7.2Reversed phase - High performance liquid chromatography for evaluation of peptides .... 35
1.7.3 Evolution of ultra-high performance liquid chromatography ............................................ 37
1.7.4 Analytical evaluation of coupling reagents during peptide synthesis ................................ 40
1.7.5 Toxicity of coupling reagents .............................................................................................. 41
1.7.6 Ipsen Manufacturing Ireland LTD. approach to the analysis of peptide coupling
reagents ....................................................................................................................................... 43
1.7.7 Use of HPLC for analysis of coupling reagents: ................................................................ 44
1.8 Aim of the thesis .......................................................................................................................... 44
2. CHAPTER 2 ................................................................................................................................ 46
DEVELOPMENT OF A UHPLC METHOD FOR THE ANALYSIS OF PEPTIDE
COUPLING REAGENTS, ADDITIVES AND ASSOCIATED BY-PRODUCTS DURING
PEPTIDE SYNTHESIS ............................................................................................................... 46
2.1 Introduction ................................................................................................................................. 47
2.2 Experimental ................................................................................................................................ 48
2.2.1 Reagents and standards ...................................................................................................... 49
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2.2.2 Instrumentation ................................................................................................................... 49
2.2.3 Solubility studies ................................................................................................................. 50
2.2.4 Determination of optimum detection wavelength ............................................................... 50
2.2.5 Evaluation of columns and mobile phase systems .............................................................. 50
2.2.6 Design of experiments ......................................................................................................... 53
2.2.7 Initial evaluation of optimum buffer pH and column temperature ..................................... 54
2.2.8 Re-optimisation of buffer pH using 10 mM ammonium formate ........................................ 54
2.2.9 Evaluation of flow rate for optimum separation ................................................................. 54
2.2.10 Re-optimisation of column temperature ........................................................................... 54
2.2.11 Evaluation of final percentage acetonitrile required for the gradient.............................. 54
2.2.12 Re-evaluation of optimum buffer concentration ............................................................... 55
2.2.13 Final optimisation of chromatographic gradient profiles ................................................ 55
2.3 Results and discussion ................................................................................................................. 55
2.3.1 Assessment of samples for analysis .................................................................................... 55
2.3.2 Design of experiments (DoE) .............................................................................................. 76
2.3.3 Evaluation of optimum pH range and column temperature ............................................... 82
2.3.4 Evaluation of column temperature using 10 mM ammonium formate pH 4.8 .................... 84
2.3.5 Analysis of additional coupling reagents ............................................................................ 85
2.3.6 Optimisation of buffer pH for separation of „Sample set B‟ ............................................... 87
2.3.7 Optimisation of flow rate for Sample set B ......................................................................... 88
2.3.8 Re-evaluation of column temperature for Sample set B ..................................................... 88
2.3.9 Evaluation of final percentage acetonitrile required for the gradient................................ 89
2.3.10 Evaluation of optimum buffer concentration .................................................................... 89
2.3.11 Final optimisation of buffer pH for Sample set B (to account for AU response) ............. 89
2.3.12 Evaluation of chromatographic gradients for separation of peptide synthesis reagents
and by-products ........................................................................................................................... 90
2.3.13 Final method for the detection of 14 peptide coupling reagents, additives and
associated by-products ................................................................................................................ 91
2.4 Conclusions ................................................................................................................................. 93
3.1 Introduction ................................................................................................................................. 95
3.2 Experimental ................................................................................................................................ 96
3.2.1 Reagents and standards: ..................................................................................................... 96
3.2.2 Instrumentation ................................................................................................................... 96
3.2.3 Effect of buffer concentration upon sensitivity ................................................................... 96
3.2.4 Adjustment of mobile phase gradient following removal of PyBrOP ................................. 96
3.2.5 Further evaluation of optimum buffer pH ........................................................................... 97
3.2.6 Specificity of the analytical method .................................................................................... 97
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3.2.7 Accuracy of the analytical method...................................................................................... 97
3.2.8 Precision of the analytical method ..................................................................................... 97
3.2.9 Sensitivity of the analytical method .................................................................................... 98
3.2.10 Linearity of the analytical method .................................................................................... 98
3.2.11 Robustness of the analytical method ................................................................................. 98
3.2.12 Solution Stability ............................................................................................................... 98
3.3 Results and discussion ................................................................................................................. 99
3.3.1 Effect of buffer concentration upon sensitivity. .................................................................. 99
3.3.2 Adjustment of mobile phase gradient following removal of PyBrOP ............................... 100
3.3.3 Further evaluation of optimum buffer pH ......................................................................... 103
3.3.4 Validation of analytical method........................................................................................106
3.3.5 Specificity of the analytical method .................................................................................. 106
3.3.6 Accuracy of the analytical method.................................................................................... 108
3.3.7 Precision of the analytical method ................................................................................... 109
3.3.8 Limit of Quantitation (LOQ) of the analytical method ..................................................... 110
3.3.9 Limit of Detection (LOD) of the analytical method .......................................................... 111
3.3.10 Linearity of the analytical method .................................................................................. 111
3.3.11 Robustness of the analytical method ............................................................................... 113
3.3.12 Solution stability ............................................................................................................. 119
3.4 Conclusions ............................................................................................................................... 122
4.0 Overall conclusion ..................................................................................................................... 124
REFERENCES .................................................................................................................................... 125
APPENDIX 1 –METHOD DEVELOPMENT: GRADIENT PROFILES .......................................... 132
APPENDIX 2 – FINAL METHOD OPTIMISATION: GRADIENT PROFILES .............................. 135
APPENDIX 3 –METHOD OPTIMISATION: RESULTS TABLES .................................................. 136
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ABSTRACT
The following thesis details the extensive development of a rapid liquid chromatography
method for the in-process determination of peptide coupling reagents used in peptide synthesis. The
determination of peptide coupling reagents, additives and associated by-products is important during
peptide synthesis to ensure the concentration of these products are below the threshold of
toxicological concern in the final peptide.
A number of column technologies and mobile phases were evaluated for the separation of the
analytes using an ultra-high performance liquid chromatography system and, a 15 minute method for
the simultaneous determination of fourteen peptide coupling reagents, additives and by-products was
established. This method was determined to be selective and capable of accurately quantitating the
amount of TMU, HOBt, HCTU, HBTU, 6-ChloroHOBt, TBTU, Oxyma Pure, COMU, DIU, DIC,
PyBOP, and TCTU in the presence of two peptides from Ipsen Manufacturing Ireland LTD.
Analytical method validation was performed as per ICH guidelines for specificity, accuracy,
linearity, precision, detection limit, quantitation limit and robustness. This rapid UHPLC method is
directly transferable onto LC-MS and the intended application of this method is for evaluation of
development peptides in Ipsen Manufacturing Ireland LTD.
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ABBREVIATIONS
AAA Amino acid analysis
ACN Acetonitrile
AcOH Acetic acid
AOMP 5-(1H-7-azabenzotriazol-1-yloxy)-3,4-dihydro-1-methyl-2H-pyrrolium
hexachloroantimonate
API Active pharmaceutical ingredient
BEH Bridged ethane hybrid
BOC tert-butoxycarbonyl
BOP Benzotriazol-1-yloxy)tris(dimethylamino)-phosphonium
hexafluorophosphate
BPMP 5-(1H-benzotriazol-1-yloxy)-3,4-dihydro-1-methyl,2H-pyrrolium
hexachloroantimonate(BDMP),2,6-Bis{[bis(2-pyridylmethyl)amino]methyl}-
4-methylphenol
Bzl Benzyl
6-ChloroHOBt 6-Chloro-1-hydroxybenzotriazole dehydrate
Cl Chlorine
COMU 1-((1-(Cyano-2-ethoxy-2-oxoethylideneaminooxy)-Dimethylamino-
Morpholinomethylene)) Methanaminium Hexafluorophosphate
cm centimetre
CV Coefficient of Variation
CZE Capillary zone electrophoresis
C18 Column having octadecyl chains of C atom
C8 Column having octyl chains of C atom
C4 Column having butyl chains of C atom
DCC N,N'-dicyclohexylcarbodiimide
DCM Dichloromethane
DIC N,N'-Diisopropylcarbodiimide
DIU 1,3-Dimethylurea
DMF Dimethylformamide
DNA Deoxyribonucleic acid
DOE Design of experiments
EDC 1-ethyl-3-(3‘-dimethylaminopropyl) carbodiimide
Exp Experiment
Fmoc 9-fluorenylmethyloxycarbonyl
g Gram
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GC Gas chromatography
GLP-1 Glucagon-like-peptide-1
GMP Good Manufacturing Practice
GPC Gel permeation chromatography
HATU 2-(7-aza-1H-benzotriazole-1-yl)-1,1,3,3-tetramethyluronium
hexafluorophosphate
HBTU O-Benzotriazole-N,N,N,N‘-tetramethyl-uronium-hexafluoro-phosphate
HCTU (2-(6-Chloro-1H-benzotriazole-1-yl)-1,1,3,3-tetramethylaminium
hexafluorophosphate)
HETP Height equivalent to a theoretical plate
HMPA Hexamethylphosphoramide
HOAt 1-hydroxy-7-azabenzotriazole
HOBt 1-hydroxybenzotriazole
HPLC High performance liquid chromatography
H2O Water
IARC International Agency For Research On Cancer
IC Ion chromatography
ICH The International Conference on Harmonisation
IMIL Ipsen Manufacturing Ireland LTD.
k* Retention factor
kg kilogram
LC Liquid chromatography
LC-MS Liquid chromatography mass spectrometry
L Litre
LD50 lethal dose50 - the dose that kills half of the tested population in an animal
model
LC50 lethal concentration50 - concentration of a chemical in air that kills half of the
tested population in a given time
LOD Limit of detection
LOQ Limit of quantitation
LPPS Liquid phase peptide synthesis
LTD Limited
MeOH Methanol
mg milligram
min Minutes
ml Millilitre
mm millimetre
9
mM millimolar
M Molar
MS Mass spectrometry
MW Molecular weight
m/z Mass to charge ratio
μL Microliter
μm Micrometer
NaHCO3 Sodium bicarbonate
nm nanometer
NMP N-methyl-2-pyrrolidone
NMR Nuclear Magnetic Resonance
ODS Octadecylsilane
Oxyma pure Ethyl (hydroxyimino)cyanoacetate
PAM resin Phenylacetamidomethyl resin
PDA Photodiode-array
PEEK Polyetheretherketone
PEG Polyethylene glycol
pH negative logarithm of H+ concentration
pKa Ionisation constant
psi per square inch
PyAOP 7-azabenzotriazol-1-yloxy)tripyrrolidinophosphonium hexafluorophosphate
PyClocK 6-chloro-benzotriazole-1-yloxy-tris-pyrrolidinophosphonium
hexafluorophosphate
PyCloP chlorotripyrrolidinophosphonium hexafluorophosphate
PyBOP Benzotriazol-1-yl-oxytripyrrolidinophosphonium hexafluorophosphate
PyBrOP Bromo-tris-pyrrolidino phosphoniumhexafluorophosphate
PyOxim Ethyl-cyano(hydroxyimino)acetato-O2)tri-1-pyrrolidinylphosphonium
hexafluorophosphate
RP Reversed phase
RP-HPLC Reversed-phase high performance liquid chromatography
Rs Resolution
RSD Relative standard deviation
SCID Severe Combined Immunodeficiency disease
SEC Size exclusion chromatography
S/N Signal to noise ratio
SFC Supercritical fluid chromatography
SPPS Solid phase peptide synthesis
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TBTU O-(Benzotriazol-1-yl)-N,N,N',N'-tetramethyluronium tetrafluoroborate
tBu tert-butyl
TCTU O-(6-Chloro-1-hydrocibenzotriazol-1-yl)-1,1,3,3-tetramethyluronium
tetrafluoroborate
TLC Thin layer chromatography
TFA Trifluoroacetic acid
TMU Tetramethylurea
TOTU O-(Cyano(ethoxycarbonyl)methylenamino)-1,1,3,3-tetramethyluronium
tetrafluoroborate
TTC Threshold of toxicological concern
UN United Nations
UPLC Ultra performance liquid chromatography
UHPLC Ultra high performance liquid chromatography
USP United States Pharmacopeia
UV Ultra violet
UV-VIS Ultra violet – visible
α Alpha
β Beta
v/v Volume by volume
v/w Weight by volume
w/w Weight by weight
% Percent
< Less than
> Greater than
ºC Degrees Celsius
Å Angstrom
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LIST OF FIGURES
Figure 1.1: Example structures of several standard amino acids.
Figure 1.2: Levels of structures of peptides and proteins.
Figure 1.3: Peptide coupling reaction scheme.
Figure 1.4: Schematic of peptide synthesis.
Figure 1.5: Schematic of solid phase peptide synthesis.
Figure 1.6: Structures of some carbodiimide peptide coupling reagents.
Figure 1.7: Mechanism of peptide bond formation through carbodiimide activation.
Figure 1.8: Structures of some Benzotriazole additives.
Figure 1.9: Structures of some Aminium peptide coupling reagents.
Figure 1.10: Structures of some Phosphonium peptide coupling reagents.
Figure 1.11: Structures of Oxyma pure and COMU.
Figure 1.12: Structures of PyOxim and TOTU.
Figure 1.13: Structures of HOBt-based and HOAt-based Immonium type coupling reagents
Figure 1.14: Schematic representation of the binding of a peptide to an RP-HPLC silica-based
stationary phase.
Figure 1.15: Van Deemter plot demonstrating the effect of particle size on column efficiency.
Figure 1.16: Fused-core particle technology.
Figure 1.17: Example calculation for determining % w/w of genotoxic impurity allowed for a 20
mg dose of peptide per week.
Figure 2.1: HPLC method development schematic.
Figure 2.2: PDA profile of reagents in „Sample set A‟.
Figure 2.3: Comparison of retention on (a) Acquity BEH C18 and (b) Acquity BEH 300 C4.
Figure 2.4: Comparison of retention on (a) Acquity HSS C18 (end capped) column and (b)
Acquity HSS C18 SB (non-end capped).
Figure 2.5: Comparison of peak shape on Acquity HSS C18 using (a) acetonitrile and (b)
methanol as organic modifier in mobile phase B.
Figure 2.6: Comparison of retention on Acquity HSS C18 using (a) sodium phosphate pH 2 and
(b) sodium phosphate pH 7 as mobile phase A.
Figure 2.7: Regression model for number of peaks resolved.
Figure 2.8: Coefficient plot for number of peaks resolved.
Figure 2.9: Coefficient plot for the % of peaks with k>2.
Figure 2.10: Coefficient plot for the % of peaks with plate count > 2,000.
Figure 2.11: Contour plot for all chromatographic performance criteria with varying pH and
buffer concentration.
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Figure 2.12: Effect of buffer pH upon retention. Buffer pH was (a) pH 2.8, (b) 3.8 and (c) 4.8, all
at a column temperature of 35 °C.
Figure 2.13: Effect of column temperature upon retention at pH 4.8. Column temperature was (a)
25 °C, (b) 35 °C and (c) 45 °C.
Figure 2.14: Comparison of column temperature of (a) 15 °C, (b) 25 °C and (c) 40 °C.
Figure 2.15: PDA profile of additional analytes. The red dotted line represents the optimum
wavelength.
Figure 2.16: Effect of mobile phase pH upon retention for Sample set B.
Figure 2.17: Final optimised separation for the detection of 14 peptide coupling reagents,
additives and associated by-products in the presence of 4 IMIL peptides
Figure 3.1: Effect of buffer concentration upon signal: noise ratio for 0.01 % w/w injections of
analyte.
Figure 3.2: Effect of flow rate upon separation. (a): 0.55 mL/min, (b): 0.50 mL/min, (c): 0.40
mL/min, (d): 0.30 mL/min, (e): 0.20 mL/min.
Figure 3.3: Effect of Peptide 1 concentration upon analyte retention. (a) Mix of reagents with
Peptide 1 at 0.5 mg/mL (b) Mix of reagents with Peptide 1 at 5 mg/mL.
Figure 3.4: Effect of pH on analyte retention.
Figure 3.5 Final optimised separation of fourteen peptide coupling reagents from a selected
commercial peptide API.
Figure 3.6: Blank chromatogram demonstrating no interfering peaks present.
Figure 3.7: Chromatogram demonstrating specificity of reagents in the presence of Peptide 1.
Figure 3.8: Chromatogram demonstrating specificity of reagents in the presence of Peptide 2.
Figure 3.9: Robustness testing on YMC Triart columns with different serial numbers – (a)
Column serial number 0210002430 and (b) Column serial number 0210002540.
Figure 3.10: Robustness testing for flow rate variation – (a) flow rate: 0.45 mL/min, (b) flow rate:
0.50 mL/min and (c) flow rate: 0.55 mL/min.
Figure 3.11: Robustness testing for column to column temperature variation - column temperature
of (a): 20 °C, (b) 25 °C and (c) 30 °C.
Figure 3.12: Robustness testing for buffer concentration variation. (a) 2.5 mM ammonium formate,
(b) 3.75 mM ammonium formate, (c) 5 mM ammonium formate and (d) 7.5 mM
ammonium formate.
Figure 3.13: Robustness testing for variation of buffer pH. (a): pH 4.5, (b): pH 4.55, (c): pH 4.6
and (d): pH 4.7.
Figure 3.14: Stability at ambient sample temperature for selected analytes.
Figure 3.15: Stability at ambient sample temperature for remaining analytes in the study.
Figure 3.16: Test mix stability at ambient sample temperature over 135 hours. (a) time-point: 0
hours (b) time-point: 135 hours.
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Figure 3.17: Comparison of solute stability (≤ 5.5 % change in peak area) at ambient temperature
and 5 oC for selected reagents.
Figure 3.18: Comparison of solute stability (≤ 5.5 % change in peak area) at ambient temperature
and 5 oC for the remaining reagents in this study.
LIST OF TABLES
Table 1.1: Toxicology classes - Hodge and Sternar scale.
Table 2.1: Chronology of method development indicating materials under investigation.
Table 2.2: Mobile phase systems under evaluation.
Table 2.3: Comparison table for columns under investigation and the corresponding gradient
profiles.
Table 2.4: Columns under investigation.
Table 2.5: Design of experiments and corresponding gradient profiles.
Table 2.6: Parameters evaluated during design of experiments for mobile phase optimisation.
Table 2.7: Chemical structure of all peptide coupling reagents, additives and by-products.
Table 2.8: USP solubility definitions.
Table 2.9: Solubility of coupling reagents, additives and associated by-products.
Table 2.10: Order of diluent addition for dissolving analytes under investigation.
Table 2.11: Absorbance (AU) of mobile phase components at selected wavelengths (nm)
Table 2.12: Comparison of columns by PQRI approach at pH 2.8 for acidic and basic compounds
Table 2.13: Gradient for a 100 mm length x 2.1 mm diameter column, 1.9 µm particle size
Table 2.14: Gradient for a 50 mm length x 2.1 mm diameter column, 1.9 µm particle size
Table 2.15: Score evaluation of Acquity HSS C18 for each mobile phase system
Table 2.16: Summary of score evaluation for all columns for each mobile phase system
Table 2.17: Summary of mass spectrometry compatible column and mobile phase systems
Table 2.18: Summary of optimum mobile phase systems (based upon selected scoring system)
Table 2.19: DoE evaluation and corresponding chromatographic performance criteria.
Table 2.20: Chemical structure of additional peptide coupling reagents and by-products added to
the study.
Table 2.21: Solubility of additional reagents added to the study.
Table 2.22: Order of diluent addition for dissolving additional reagents.
Table 2.23 Final optimised gradient program.
Table 3.1: Optimum gradient profile for buffer optimisation.
Table 3.2: Results of gradient optimisation following the removal of PyBrOP from the mixture
Table 3.3: Final optimised gradient after removal of PyBrOP from the test mix.
Table 3.4: Accuracy of each analyte at 80 %, 100 % and 120 % of the specified range
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Table 3.5: Precision, repeatability and intermediate precision results
Table 3.6: Limit of quantitation results
Table 3.7: Limit of detection results
Table 3.8: Linearity of analytical method
Table 3.9: Determination of relative response factors
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ACKNOWLEDGEMENTS
Firstly, I would like to extend my gratitude to Ipsen Manufacturing Ireland LTD., and
especially Dr. Tom Loughman for giving me the opportunity to obtain a research masters. I wish to
thank all of my colleagues in Ipsen Manufacturing Ireland LTD., particularly all of my colleagues
within the CMC-APID group. I would like to express my sincere gratitude to my supervisor Dr.
Damian Connolly for the useful comments, remarks and engagement through the learning process of
this master thesis.
Furthermore I would like to thank my loved ones, who have supported me throughout entire
process. In particular, I would like to thank Kevin Kerrigan and my Mother, Sheila Barry for all their
help in completing this research masters.
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______________________________________________________________________
Chapter 1
Literature Review
__________________________________________________________________________
17
1.1 Overview of peptides and proteins
Peptides and proteins are co-polymers of amino acids that are covalently linked through a
peptide bond [1]. They differ from each other by the number and sequence of the constituent amino
acids [1]. Those with low molecular weights, typically consisting of less than 50 amino acids, are
called peptides [2]. Peptides composed of fewer than 20 amino acid residues are known as
oligopeptides while those with more than 20 but less than 50 amino acid residues are known as
polypeptides [3]. The term protein describes a macromolecule incorporating more than 50 amino acid
residues [3]. Peptides and proteins are made up of a possible combination of 20 proteinogenic α-
amino acids [3]. Nineteen of the standard α-amino acids are composed of a central α-carbon atom to
which a carboxyl group, an amino group, a hydrogen atom and a side chain R are attached
[4]. The R
represents a side chain specific to each amino acid [4]. The 20
th standard α-amino acid, proline, differs
from the other amino acids as its amino group is secondary, formed by ring closure between the R
group and the amino nitrogen as shown in Figure 1.1 [2]. Proline is an amino acid that confers rigidity
in a peptide or protein, as rotation about the carbon atom is not possible [2]. All of the 20 amino acids,
with the exception of glycine, are chiral, due to the presence of at least one stereogenic carbon and
they all belong to the L-stereochemical series [5].
Figure 1.1 Example structures of several standard amino acids [2]
Peptides and proteins have well defined three dimensional structures [2]. These structures are
made up of a primary structure, which represents the sequence of amino acids and a secondary
structure, which is the folding of the amino acid chain into patterns such as α-helix and β-pleated
sheets, as shown in Figure 1.2 [2]. The α-helix pattern is a rod-like structure formed when the amino
acid chain twists into a right-handed helical conformation [2]. The β-pleated sheets pattern is the
formation of two or more polypeptide chains lining up side by side [2]. The backbones of the peptides
and proteins then bend and fold to form their tertiary structure [6]. Some proteins, unlike peptides,
can be composed of several polypeptide chains and this is referred to as a quaternary structure [2].
18
Figure 1.2 Levels of structures of peptides and proteins [6]
Peptides and proteins play a key role in a variety of biological and physiological processes in
living organisms [7]. They act as hormones and neurotransmitters in intracellular communication, act
as antibiotics in the immune system and are involved in the transport of numerous substances through
biological membranes [7]. Examples of this can be seen with insulin and glucagon, which are used to
regulate the level of glucose in the blood [7,8]. Insulin, the first peptide to be administrated
therapeutically, decreases the level of blood glucose by increasing its uptake into the liver where it is
stored as glycogen and broken down by glucagon [8,9]. The amino acid sequences that make up
peptides and proteins control and direct all aspects of cellular functions and coordinate most
intercellular communication within living organisms [10]. Peptides and proteins are the only class of
biological molecules that offer such a range of chemical diversity and demonstrate the potential for
addressing a growing range of medical challenges [10].
1.2 The use of peptides as drug candidates
Peptides and proteins can influence endocrine, neurological, immune and enzymatic
processes with high specificity [3]. It is for this reason that peptides and proteins are being used
therapeutically in areas such as regulation of fertility, control of pain, cancer therapy, and the
stimulation of growth, cardiovascular problems, and mental illness [3]. Peptide-based drugs tap into
the direct hard wiring of human physiology, yielding substantial benefits for drug therapies [11].
Current therapeutic peptides include glucagon-like-peptide-1 (GLP-1) and somatostatin analogues [9].
GLP-1 has insulin-releasing properties, suppresses glucagon levels and also delays gastric emptying
for the treatment of diabetes while somatostatin analogues are used for the treatment of cancer and
acromegaly [9].
Peptide drug candidates rely on the activation or inhibition of a biochemical process, by the
specific recognition of, and interaction with, natural receptors [3]. Peptides have numerous advantages
as drug candidates due to their high potency, minimized drug-drug interactions, low toxicity and
biological diversity [12]. Peptides have the potential to penetrate deeper into tissues in comparison to
19
proteins and antibodies due to their smaller size [13]. Peptides also demonstrate advantages over small
molecules due to greater efficacy, selectivity, specificity, and reduced half-life, which means few
peptides accumulate in tissues [13]. They are composed of naturally occurring or metabolically
tolerable amino acids and are generally non-toxic [10]. Therapeutic peptides are mainly receptor
agonists and therefore only small quantities of peptide are required to activate the target receptors
[13]. Agonist drugs activate receptors by eliciting a biological effect which can be stimulatory or
inhibitory, and in contrast, antagonist drugs are agents that block-receptor-mediated effects elicited by
hormones, neurotransmitters or agonist drugs by competing for the receptor occupancy [14]. The
proportion of a peptide drug available for binding is influenced by the amino acid composition and
sequence, the peptide length and peptide flexibility, as well as characteristics such as solubility, pH
and the peptide formulation [15,16].
Peptides as drug candidates are not without their disadvantages. They demonstrate low oral
bioavailability, which is the rate and extent to which the active ingredient is absorbed from a drug
product [13,15]. Peptides also demonstrate a short half-life in the body due to degradation by
proteolytic enzymes of the digestive system and are rapidly removed from the circulation system by
the liver and kidneys [13]. Their hydrophobicity means they have restricted ability to cross
physiological barriers and their high conformational flexibility results in the lack of selectivity for
interactions with receptors or targets [13]. Lack of specificity for the target or receptors can result in
activation of several targets, leading to side effects and possible immunogenic effects [13]. Enzymes
such as peptidases are involved in the rapid degradation of peptides in the body [13]. The lumen of the
small intestine is the largest threat to degradation of peptides as it contains gram quantities of the
peptidase enzymes [13]. The epithelial cell membranes also contain over 15 peptidases which are
specific to degrade both peptides and proteins [13]. As a result, peptides are administered by
subcutaneous, intramuscular or intravenous routes to avoid the gut barrier and typically, patients
require chronic self-injection [10,13]. Alternative routes of administration and new synthetic
strategies are critical for the use of peptides as drug candidates [13].
1.3 Advances in the use of peptides as drug candidates
In the 1980s, pharmaceutical companies focused on small molecules rather than peptides due
to their demonstrated advantages in-vivo stability and pharmacokinetics [17]. However in the late
1990s, the unexpected toxicity and cross-reactivity of small molecule drugs turned the focus back to
peptides, which typically demonstrate a low toxicity profile. [17]. Now in the 21st century, peptide-
based drug targets are being identified at a rapid pace. The number of peptides going into clinical
trials has increased from approximately 1.2 % of drugs per year in the 1970s, to approximately 16.8 %
of drugs per year in the 2000s [18]. This increase is due to advances in the administration of peptides
such as the development of peptides encapsulated in biodegradable polymers in the 1980s, which
20
resulted in peptide injections only being required at extended intervals [10]. This was a significant
milestone for increasing the acceptability of peptides as drug candidates [10]. Alternative routes of
delivery are still a focal point of research in peptides including inhaled, buccal, intranasal and
transdermal routes of administration [9].
Although formulation and application systems are important to improve peptide drug
candidate possibilities, a major strategy in peptide chemistry is directed towards the chemical
modification of peptides to increase their chemical and enzymatic stability and to also increase their
activity and selectivity towards the receptor [19]. Peptidomimetic modifications are typically used to
overcome the unattractive pharmacological properties of native peptides, turning a peptide structure
into a non-peptide drug, providing a more conformationally constrained and thus, more stable peptide
[17,19]. Typical peptidomimetic approaches used are pseudo-peptides and peptide bond modification,
in which the peptide bonds have been replaced with other chemical groups, known as an amide bond
surrogate [17]. The amide bond surrogates possess three-dimensional structures similar to the peptide,
but they differ significantly from peptides in relation to polarity, hydrogen bonding capability and
acid-base character [17]. The amide bond surrogates aim to completely prevent protease cleavage of
the amide bond and therefore result in increasing resistance of peptides to degradation and elimination
and also increasing their selectivity and bioavailability [13,17]. The development of unnatural amino
acids and new synthetic strategies to produce cyclised peptides are also valuable tools developed to
overcome the drawbacks of peptide therapeutics [18] Cyclised peptides demonstrate improved
chemical stability and thus extend the biological half-life compared to their linear counterpart [20].
Conjugation of a peptide with a fatty acid or polyethylene glycol (PEG) derivative can result in
increased half-life, increased bioavailability and also result in more specific binding [12]. PEG
consists of a repeating chain of ethylene oxide, and once bound to the peptide; each sub-unit of the
PEG becomes tightly associated with two or three water molecules, rendering the peptide more water
soluble [21]. The globular structure of PEG protects the peptide from proteolytic degradation and can
also aid in drug delivery [21].
1.4 Sources of peptides
Natural sources of peptides, such as extraction from humans and plants, can provide a great
variety of peptides, however miniscule amounts can typically only be isolated [3,22]. This is partially
due to the low concentration of peptide mediators in some tissues or limited availability of human
tissue sources [19]. Contamination of tissue with pathogenic viruses also restricts the use of natural
sources for the isolation of peptides [19]. As a result, chemical synthesis, recombinant technology,
cell-free expression systems or enzymatic synthesis are other approaches typically used to generate
peptides for drug candidates [13]. Each of these techniques has their advantages and disadvantages
but generally, the size of the peptide determines the most suitable technology for its production [7,13].
21
Recombinant technology is currently used for the manufacture of a small number of peptides due to
demands of significant personnel input into process development, production, quality assurance and
regulatory affairs [10]. However, it is expected that recombinant technology will play an increasingly
important role in the future of peptide manufacturing due to larger quantities being required [10].
Insulin, composed of approximately 50 amino acids, was formally obtained from porcine and bovine
pancreatic tissue [3]. Sensitisation became an issue with patients as pig and beef insulin is not
identical to human insulin and as a result, human insulin was subsequently prepared commercially by
recombinant DNA technology [3]. Immunological incompatibilities of peptide drugs from animal
sources have been observed, and as a result, significant emphasis has been placed on the use of
chemical synthesis for the production of peptides [19]. Chemical synthesis is the only technique
which permits the use of unnatural amino acids and the production of large quantities of pure peptide
[7,13].
1.5 Chemical synthesis of peptides
Chemical synthesis is currently the preferred technique for manufacturing peptides as it offers
a much wider chemical diversity than peptides produced recombinantly. This chemical diversity is
partially due to the use of unnatural amino acids and pseudo-peptide bonds [13]. Peptide synthesis
involves the formation of a peptide bond between the two amino acid segments by a peptide coupling
reaction [23]. A peptide coupling reaction involves the activation of the carboxylic acid moiety of an
amino acid which then reacts with the amine moiety of another amino acid forming a peptide bond as
demonstrated in Figure 1.3 [24].
ROH
O
NH2
+
R'
OH
O
NH2
R
O
NH2
R'
O
OH
Amino acid I Amino acid II Peptide
Peptide couplingreagent
-H2O
Figure 1.3 Peptide coupling reaction scheme [25]
In order to activate the carboxylic acids, peptide coupling reagents are required which
generate compounds such as active esters, carbonic anhydrides or acid chlorides [26]. Different
strategies have been employed to aid the formation of a peptide bond, usually involving protection,
activation, coupling and deprotection steps [23]. During the formation of a peptide bond, one specific
amide bond is desired but there is the potential for three amide bonds to form [27]. Therefore
protecting groups are used for all functional groups except those that are involved in the specific
22
amide bond formation to ensure they do not react and only the desired amide bond is formed [27]. As
demonstrated in Figure 1.4, two amino acids with protecting groups P1 and side chain protection P2,
will react to yield a fully protected dipeptide bond in the presence of the coupling reagents [8]. The
protecting group (either P3 or P4) can be removed, depending on whether the polypeptide chain is to
be extended at the N-terminus or the C-terminus [8].
Figure 1.4 Schematic of peptide synthesis [8]
The protecting groups are a crucial part of peptide synthesis, the absence of which will result
in the possible formation of a mixture of di-, tri- and polypeptides [5]. The protecting groups need to
have the ability to be selectively removed during the peptide synthesis [8]. There are three type of
protecting groups, N-terminus, the C-terminus, and the side chain protecting groups [5]. N-terminus
protecting groups are typically urethane based, such as tert-butoxycarbonyl (Boc) group, which is
typically removed with moderately strong acid, and 9-fluorenylmethyloxycarbonyl (Fmoc) group,
which is removed under base condition. The N-terminus protecting groups are typically temporary as
they are removed in order to grow the peptide, which generally proceeds in the C-N direction [5]. Side
chain protecting groups are called ‗permanent‘ protecting groups as they are never removed during
the synthesis process and are usually based on benzyl (Bzl) or tert-butyl (tBu) groups [5]. In relation
to the C-terminus protecting group, this is dependent on what type of peptide synthesis approach is
used [5]. Chemical synthesis involves either a solid phase peptide synthesis (SPPS) or a liquid phase
peptide synthesis (LPPS) approach. For SPPS, the C-terminal protecting group is a polymer and in
LPPS, tert-butyl esters, benzyl esters and phenyl esters can all be used as protecting groups [5].
23
1.5.1 Liquid phase peptide synthesis (LPPS)
Liquid phase peptide synthesis (LPPS) is the controlled formation of a peptide by the
coupling of amino acids in solution [5]. Isolation, purification and characterisation are required after
each amino acid addition in LPPS; therefore the process is considerably longer than SPPS [5]. This
process can prove advantageous when large quantities are targeted and also, any unwanted side
products, such as incomplete deprotection or coupling reactions, are easily detected during the
isolation and characterised after each step [12,5]. This process is not suitable for small peptides as it
would result in a considerable investment in time and energy for minimal yield and also, the solubility
of the peptide decreases with increasing chain length, which can result in intermediates that are so
insoluble that they render their chemical reactions effectively impossible [5,28]. Attempts have been
made to overcome the problems associated with the classical peptide synthesis in solution and led to
the invention of solid phase peptide synthesis (SPPS) [5].
1.5.2 Solid phase peptide synthesis
Solid phase peptide synthesis was discovered by Bruce Merrifield in 1963, where he
covalently attached an amino acid to an insoluble support and elongated a peptide chain from the
support—bound residue [28]. The theory of SPPS involves growing the peptide on an insoluble
support in which the by-products are removed after each step [7]. The LPPS problems are no longer
applicable in SPPS, as the isolation of intermediates is no longer required and the problem of poor
solubility of the intermediates is removed as the growing peptide remains on the insoluble support
until the synthesis has been completed [5]. Linkage of the peptide to the insoluble support must be
strong enough to ensure it does not break during the course of subsequent peptide synthesis, but still
have the ability to be cleaved at the end of the process to liberate the final peptide [8]. The insoluble
support must be chemically inert to all of the reagents and solvents used during the peptide synthesis
and must not interact physically, with them or the peptide itself [5]. The insoluble support is typically
a cross-linked polystyrene material and the cross-linking results in the polymer being insoluble in
organic solvents [27]. The polymers, known as resin, typically come in the form of small beads [27].
The polystyrene support beads are typically 20-50 μm in diameter but are swollen in organic solvents
such as dichloromethane (DCM) or dimethylformamide (DMF) [29]. The insoluble support must have
an appropriate functional group or be capable of functionalisation, to which the amino acid or a linker
is attached [28]. A linker can be used which acts as a bifunctional spacer to connect the first amino
acid to the solid support, providing more flexibility to modify the properties of the peptide-resin
anchorage [5,28]. An example of a linker is 4-(bromomethyl)phenylactic acid which is incorporated
into an aminomethyl polystyrene solid support, giving rise to phenylacetamidomethyl resin (PAM
resin) [5].
24
The main SPPS strategy is sequential synthesis which involves the stepwise addition of amino
acids to achieve the final peptide sequence [13]. It involves repetitive coupling and deprotection steps
to introduce the amino acids as shown in Figure 1.5 [28].
Figure 1.5 Schematic of solid phase peptide synthesis [8]
Once the desired peptide length is achieved, the peptide is cleaved from the solid support
[28]. Sequential synthesis is a very fast and efficient way to synthesise peptides, however the growing
peptide can fold over onto itself, or aggregate with a neighbouring chain which can result in poor
yield or a truncated peptide, and therefore careful monitoring of the process is required [30]. SPPS has
a wide variety of applications for drugs on the market today; however its limitations make the
assembly of large peptides particularly challenging [5]. The peptide remains on the solid support for
the entire process and if a coupling reaction fails to go to completion, then the final product will
contain deletion peptides, which tend to be difficult to remove [8]. This problem is typically overcome
by the confirmation of the completion of each coupling reaction during the synthesis process [28].
The unreacted primary amines react with reagents such as ninhydrin and bromophenol blue, which
can be monitored qualitatively or quantitatively [28]. A result of approximately 100 % completion
reaction is required for each amino acid coupling to ensure a high yield following the peptide
synthesis process [8]. If a low yield is achieved for each coupling reaction then the accumulative yield
would be detrimental to large peptide sequences and could result in a significantly low yield at the end
of the synthesis process [5]. These problems have resulted in the use of the production of large
peptides and proteins being produced chemically by another mode of SPPS, known as convergent
synthesis [5].
Convergent synthesis is the formation of independent peptide sequences that are then cleaved
from the solid support, purified and characterised, and linked together by condensation in solution to
form the final peptide product [13,5]. It utilises the advantages of both solution phase and solid phase
25
peptide synthesis, with regards to purification and characterisation of intermediates throughout a more
rapid process [5]. Convergent synthesis is typically used for peptide sequences that contain > 50
amino acid residues and is advantageous for repetitive sequences and hydrophobic peptides [13]. It
generally gives higher overall yields than sequential synthesis and involves the manipulation of small
and easily handled peptide fragments [27]. When construction of the target peptide is complete,
cleavage and purification are performed as per sequential peptide synthesis [5].
Regardless of the type of chemical synthesis used, the formation of the peptide bond is crucial
for obtaining an efficient and economic peptide production process [31]. Success in peptide synthesis
is highly dependent on the coupling strategy employed [32]. A fast peptide synthesis is desired during
peptide manufacture, and this is affected by the rate of amino acid acylation and is heavily dependent
on the properties of the coupling reagents [33]. The synthesis of peptides is a well-established
process; however the combination of the 20 proteinogenic amino acids and the increasing number of
unnatural amino acids makes each peptide synthesis unique, requiring closer attention to each amino
acid coupling and coupling reagents employed [31].
1.6 Peptide coupling reagents
A good coupling reagent is one that works with a high efficiency for a wide variety of
peptides, can be used in both solid and liquid phase synthesis and can also be used in stoichiometric
quantities [31]. The coupling reagent should demonstrate high stability, result in minimal side
reactions and produce by-products that can be completely removed by solvent extraction [31]. Ideally
they will be reasonably priced, have a long shelf life and involve a chemistry process that is adaptable
for up-scaling [31]. The ideal peptide coupling reagent and its by-products must be safe for the user
and the environment [34].
Highly effective peptide coupling reagents are essential in peptide synthesis; otherwise the
formation of impurities can occur, which can result in an increase in the time required for the
purification of the peptide [31]. Peptide racemisation is a problem related to the coupling reaction
[31]. Racemisation is a process that can occur on the C-terminal amino acid residues during a
coupling reaction where the chiral α-carbon is converted from the L form to a D/L form mixture
[25,27]. Racemisation is a serious problem in peptides as the biological activity of most peptides is
critically dependent on the stereochemistry [8]. It is possible that a change in one amino acid residue
in a peptide from the L to the D form can result in the compound being biologically inactive [8]. The
use of additives, the use of solvents with low dielectric constant, and the reduction in the time of pre-
activation of the carboxylic acid will all reduce the formation of racemisation peptides [31]. Deletion
peptides, which lack one or more residues, are impurities that can also occur if the coupling reagent is
not effective [31]. Truncated peptides, where the N-terminus is irreversibly blocked preventing further
elongation, occurs if the resin is over-dried and terminated peptides can also occur in the presence of
26
acetic acid, trifluoroacetic acid or guanidine derivatives from aminium salts [31]. Impurities formed
during peptide synthesis are often difficult to detect as they display similar chromatographic
properties as the peptide, therefore it is critical to optimise the coupling reactions [31]. Purification by
preparative HPLC has been proven to be a time consuming step in the peptide manufacture process,
therefore optimisation of the coupling reagents is critical to increase the crude purity going into
purification [12]. Each reagent is classified into several different types, namely carbodiimides, onium
salts such as phosphonium and uronium/aminium salts, and immonium coupling reagents [25].
1.6.1 Carbodiimide peptide coupling reagents
The era of peptide coupling reagents began in 1955 with the use of dicyclohexylcarbodiimide
(DCC) [31]. DCC belongs to a group of coupling reagents known as carbodiimides, which also
includes diisopropylcarbodiimide (DIC) and 1-ethyl-3-(3‘-dimethylaminopropyl) carbodiimide
(EDC), the structures of which are outlined in Figure 1.6 [31].
Figure 1.6 Structures of some carbodiimide peptide coupling reagents [35]
Carbodiimides contain two nitrogen atoms, which are weakly alkaline, and this triggers a
reaction with the carboxylic acid of the amino acid to form O-acylisourea [35]. The carbodiimides
reagents are relatively inexpensive and their active species, O-acylisourea is moderately reactive, as
seen in the schematic for a carbodiimide reaction in Figure 1.7 [25]. Carbodiimide coupling reactions
are usually carried out with ratios of N-protected amino acid to the carbodiimide coupling reagent of
2:1 in the presence of dimethylformamide (DMF) or dichloromethane (DCM) [5]. They are associated
with high racemisation and low yields due to the formation of N-acylurea, as shown in Figure 1.7,
which has poor reactivity [31]. DCC is incompatible with Fmoc/tBu protecting groups in solid phase
chemistry due to the insolubility of dicyclohexylurea in common solvents such as DMF and DCM, in
which it precipitates from the reaction mixture [31,36]. However, DCC has been proven to be a very
useful reagent for solution phase peptide reactions [37].
27
Figure 1.7 Mechanism of peptide bond formation through carbodiimide activation [38,39]
1.6.1.1 Benzotriazole additives for carbodiimide reactions
In the 1970‘s, 1-hydroxybenzotariazole (HOBt) was introduced as an additive to the
carbodiimide reactions to suppress racemisation and the formation of side reactions [31]. Adding an
equivalent of HOBt, results in reaction of HOBt with the O-acylurea formed in the carbodiimide
reaction, to form OBt active esters [26]. The OBt active esters are less reactive than O-acylisourea
formed with DCC, and therefore are less prone to racemisation and are more stable [35]. Alongside
reducing racemisation, HOBt was also proven to be a rate enhancer for the reaction [24]. However,
HOBT with DCC also yielded undesired by-products such as diazetidine [26]. In 1994, another
racemisation suppressant was developed, 1-hydroxy-7-azabenzotriazole (HOAt), which was
demonstrated to be more efficient than HOBT in relation to yield and racemisation suppression [26].
This was reportedly due to the anchimeric assistance caused by the pyridine ring present in HOAt
[23]. The nitrogen on the HOAt also provides a neighbouring group effect that can increase reactivity
28
and reduce racemisation [24]. Another additive, 6-chloro-1-hydroxybenzotriazole (6-ChloroHOBt)
was also used as an additive to the carbodiimide reactions, providing a good compromise between
HOAt and HOBt with regards to reactivity and price [35].
Figure 1.8 Structures of some benzotriazole additives [25,31]
Unfortunately, carbodiimide coupling reagents have been shown to demonstrate skin irritating
properties and some of the benzotriazole based additives have also been proven to cause skin
irritation, as well as contact dermatitis, sensitisation and an allergic reaction in the respiratory tract
[31]. The United Nations (UN) reclassified HOBt as a desensitized explosive and the material can no
longer be shipped economically, however HOBt hydrate can be shipped safely and is used in its place
[40]. HOAt was also determined to be very unstable with high sensitivity to friction and electrostatic
discharge and therefore has a risk of burning or exploding. These safety developments have been the
driving force for the extensive research into alternative, non-hazardous peptide synthesis reagents
[40].
1.6.2 Onium salts as peptide coupling reagents
Onium salts, mainly aminium/uronium and phosphonium, were developed based on 1H-
benzotriazoles of HOBt, HOAt and 6-ChloroHOBt [26]. These have become the preferred choice for
liquid and solid phase synthesis as they are much safer than the carbodiimide coupling reagents with
benzotriazole additives [32]. Onium coupling reagents based on HOAt were reported to be superior to
those based on HOBt in terms of efficiency and control of racemisation [26]. Derivatives based on
1H-benzotriazoles of 6-ChloroHOBt have also been demonstrated to be less hazardous and more
reactive than HOBt [32]. They generate 6-chloro-1-benzotriazolyl esters which are more reactive than
OBt esters due to the increased acidity of 6-ChloroHOBt relative to HOBt [40]. There are two types
of onium salt coupling reagents, Aminium/Uronium salts and Phosphonium salts, as detailed below.
1.6.2.1 Aminium/Uronium salts
The most powerful onium salts are the aminium/uronium salts based on the HOBt/HOAt
system [26,32]. These salts are prepared by reaction with the 1H-benzotriazoles with the
chloroformamidinium salt derived from a urea, such as tetramethylurea (TMU) [41]. The carbon
skeleton structure has a determining role in the efficiency of the reagent for the activation step [42].
29
Benzotriazole-N,N,N‘,N‘-tetramethyl-uronium-hexafluoro-phosphate (HBTU), based on HOBt, is an
uronium salt that was discovered in 1978, followed by various HBTU analogues such as O-
(Benzotriazol-1-yl)-N,N,N',N'-tetramethyluronium tetrafluoroborate (TBTU) as shown in Figure 1.8
[24]. A hexafluorophosphate and tetrafluoroborate anion is used as a non-nucleophilic counter ion in
uronium/aminium reagents, the tetrafluoroborate salts are more soluble [24]. The main difference
between the two coupling reagents, HBTU and TBTU, is the counter ion, which has no significant
influence on the coupling rate or racemisation [24]. 2-(7-aza-1H-benzotriazole-1-yl)-1,1,3,3-
tetramethyluronium hexafluorophosphate (HATU), developed in 1993, is based on 1H-benzotriazoles
of HOAt [33]. It is the most reactive aminium salt and has even been viewed as the most efficient
coupling reagent available for peptide synthesis [43]. However, its use is minimal in industry due to
its expensive cost and its use is often reserved for very difficult couplings [33,43]. HBTU/TBTU in
the presence of 6-ChloroHOBt is a recommended alternative to the expensive HATU [44].
2-(6-chloro-1H-benzotriazole-1-yl)-1,1,3,3-tetramethylaminium hexafluorophosphate
(HCTU), established in 2002, and O-(6-chloro-1-hydrocibenzotriazol-1-yl)-1,1,3,3-
tetramethyluronium tetrafluoroborate (TCTU) are aminium salts based on 6-ChloroHOBt [34].
HCTU/TCTU reagents are more reactive and less hazardous than HBTU/TBTU salts, due to the
presence of a chlorine atom that stabilises the structure [36]. HCTU demonstrates efficiency close to
HATU, without the associated cost, and results in higher purity peptides than HBTU and TBTU [33].
There are limits to using the uronium/aminium salts as peptide coupling reagents [32]. Their high
reactivity may lead to side reactions, usually during slow couplings such as cyclisations or in the
introduction of hindered residues [32]. Uronium/aminium salts can react with the hindered carboxylic
components leading to a guanidine derivative which can terminate the peptide sequence [36]. This
guandinylation is particularly problematic when carboxyl activation is slow, such as cyclisation
reactions [45]. Uronium/aminium reagents are generally less stable than phosphonium reagents
(discussed in Section 1.6.2.2) in the presence of base. [24]. A detailed discussion as to the advantages
and disadvantages of the coupling reagents (i.e. coupling efficiency, etc.) is outside the scope of this
thesis because no synthetic work was performed during this thesis. The structures of some aminium
peptide coupling reagents are outlined in Figure 1.9.
Figure 1.9 Structures of some aminium peptide coupling reagents [24,25,32]
30
1.6.2.2 Phosphonium salts
The second group of onium salts based on 1H-benzotriazoles of HOBt and HOAt are phosphonium
salts [26]. They differ from other onium salts in the nature of the electrophilic core as they have a
positively charged phosphorus centre [32]. Phosphonium salts demonstrate similar reactivity to the
aminium/uronium salts; however they do not undergo peptide termination in excess [32].
Benzotriazole-1-yl-oxy-tris-(dimethylamino)-phosphonium hexafluorophosphate (BOP) was the first
HOBt-phosphonium salt developed, however its use is limited due to respiratory toxicity and
carcinogenicity [26]. It is an excellent coupling reagent but hexamethylphosphoramide (HMPA), a
toxic compound, is formed as a by-product [35]. A pyrrolidino derivative of BOP, benzotriazol-1-yl-
oxytripyrrolidinophosphonium hexafluorophosphate (PyBop) was then developed [26]. This is a
useful peptide coupling reagent for the activation of hindered amino acids, where its aminium
analogue would result in the formation of guanidine derivatives, and terminate the peptide chain [31].
Alongside PyBOP, chlorotripyrrolidinophosphonium hexafluorophosphate (PyCloP) and bromo-tris-
pyrrolidino phosphoniumhexafluorophosphate (PyBrOP) were developed in order to prevent the
generation of undesirable HMPA [35]. 7-azabenzotriazol-1-yloxy) tripyrrolidinophosphonium
hexafluorophosphate (PyAOP), derived from HOAt, is the most reactive phosphonium salt [31]. Both
PyBOP and PyAOP coupling reagents can be used in excess in a coupling reaction but unfortunately
there are limitations with using these phosphonium salts also, PyAOP is relatively expensive and
PyBOP, its cheaper counterpart, demonstrates lower reactivity [36]. 6-chloro-benzotriazole-1-yl-oxy-
tris-pyrrolidino-phosphonium hexafluorophosphate (PyClocK) is a phosphonium salt of
6chloroHOBt, which is ideal for difficult or hindered reactions where the carboxyl activation is slow
[32]. The structures of some phosphonium peptide coupling reagents are outlined in Figure 1.10. The
stability of phosphonium salts can be correlated to their reactivity [36]. PyBOP and PyClocK are
more stable and less reactive than PyAOP [36]. PyClocK was reported to perform better than PyBOP
in terms of racemisation control and efficiency [36]. However, in the absence of base, the hydrolysis
of PyClocK was demonstrated to be more significant than PyBOP
[26].
Figure 1.10 Structures of some phosphonium peptide coupling reagents [25,46]
31
1.6.3 Oxyma based additives
Ethyl 2-cyano-2-(hydroxyimino) acetate (Oxyma pure), established in the 1970‘s, can be used
in place of HOBt in carbodiimide-mediated coupling reactions [32,40]. Oxyma pure derivatives have
demonstrated higher stability than the benzotriazole derivatives, HATU and HBTU [47]. Oxyma pure
is a less hazardous compound in comparison to its explosive counterpart benzotriazole-based reagents,
however thermal stability of this compound is relatively low in comparison to HOBt hydrate and
HOAt [46]. Oxyma pure demonstrates a remarkable capacity to inhibit racemisation, as well as high
coupling efficiency [40,46]. The structure of Oxyma pure can be seen in Figure 1.11.
1.6.4 Oxyma based uronium salts
1-((1-(Cyano-2-ethoxy-2-oxoethylideneaminooxy)-Dimethylamino-Morpholinomethylene))
Methanaminium Hexafluorophosphate (COMU) is a third generation of uronium-type coupling
reagent based on Oxyma pure and a morpholino carbon skeleton [47]. The presence of the morpholino
moiety (as shown in Figure 1.11) has an impact on the polarity of the carbon skeleton and therefore
influences the stability, solubility, and reactivity of the reagent [47].
Figure 1.11 Structures of Oxyma pure and COMU [47]
The morpholino carbon skeleton acts as a proton receptor, and the Oxyma moiety acts as a
leaving group to provide a superior, and safe amide formation [47]. The proton acceptor moiety
allows the use of one equivalent of base during coupling, resulting in reduced racemisation without
impacting yield or reaction rate [48]. The by-products of COMU are water soluble and easily removed
[23]. Like Oxyma pure, COMU is a less hazardous compound in comparison to benzotriazole-based
reagents, and is less likely to cause an allergic reaction such as contact dermatitis or asthma [48]. It is
reported that COMU has high solubility in most usual solvents, and is applicable for both solid and
liquid phase synthesis [48]. Overall, it is reported to be more efficient than benzotriazole-based
32
reagents in terms of racemisation suppression, stability, solubility, and coupling effectiveness,
however this is dependent on the peptide sequence and amino acids used [49]. COMU is used in the
same way as PyBOP, HATU, and HBTU, but it generates an ester of Oxyma pure instead of
benzotriazolyl esters [40].
O-(Cyano(ethoxycarbonyl)methylenamino)-1,1,3,3-tetramethyluronium tetrafluoroborate
(TOTU), another coupling reagent based on Oxyma pure, exhibits many similar properties to COMU
[40]. It has high reactivity, solubility, stability and low explosivity [40]. The by-products are water
soluble, making TOTU ideal for liquid phase synthesis [40].
Ethyl-cyano (hydroxyimino) acetato-O2) tri-1-pyrrolidinylphosphonium hexafluorophosphate
(PyOxim) is a cost effective alternative to COMU [45]. It has been reported to combine high
reactivity and solubility with moderate stability, to make an ideal coupling reagent [50]. Like COMU,
it generates Oxyma pure esters and it mediates coupling with low racemisation [45]. PyOxim
demonstrates excellent solubility in dimethylformamide (DMF) and N-methyl-2-pyrrolidone (NMP),
along with low potential for causing allergic reactions [45].
Figure 1.12 Structures of PyOxim and TOTU [24]
1.6.5 Immonium reagents
Immonium reagents are peptide synthesis reagents which are prepared via modifications of
uronium reagents [25]. The structural distinction is due to the replacement of the amino group of the
central atom in uronium with a hydrogen, an alkyl or an aryl group [25]. The HOBt and HOAt
immonium coupling reagents include 5-(1H-benzotriazol-1-yloxy)-3,4-dihydro-1-methyl 2H-
pyrrolium hexachloroantimonate (BDMP), 2,6-Bis{[bis(2-pyridylmethyl)amino]methyl}-4-
methylphenol (BPMP) and 5-(1H-7-azabenzotriazol-1-yloxy)-3,4-dihydro-1-methyl 2H-pyrrolium
hexachloroantimonate (AOMP) [51]. These reagents demonstrate rapid reaction speed, low
racemisation and good yields and they have been shown to be more efficient then the HOBt and
HOAt- derived uranium/aminium and phosponium salts [51].
33
Figure 1.13 Structures of HOBt-based and HOAt-based immonium type coupling reagents [51]
1.6.6 Cleavage, deprotection and isolation of the peptide
On completion of the synthesis of the peptide, the peptide needs to be cleaved from the resin
and the protecting groups need to be removed from the side chains [52]. The cleavage conditions are
critical; they need to be sufficiently vigorous to remove the peptide from the resin and, at the same
time, sufficiently mild to allow sensitive structural features to survive [5]. The chemical method
employed to cleave the peptides depends on the nature of the cleavable linker attaching the peptide to
the support, the nature of the protecting groups and also the reactive properties of the unprotected
side-chains [5,52]. Acidolysis is typically the process used and this involves treating the bound
peptide residue with acid [5]. Strong acid such as liquid hydrogen fluoride is used for peptides
synthesised using the Boc/Bzl approach and a weaker acid, such as trifluoroacetic acid is used for
peptides synthesised with the Fmoc/tBu approach [5]. As the side chain-protecting groups are
removed during the cleavage, the reaction solution is rich in potent electrophilic alkylating species,
which potentially lead to the alkylation of susceptible residues [5]. In order to prevent this occurring,
appropriate scavengers, such as anisole and thiol derivatives, must be added to the reaction, isolating
the electrophiles and therefore, minimising modification or destruction of the sensitive amino acids
[3].
On completion of cleavage of the peptide from the resin, purification of the peptide solution is
required to remove side products arising from modification of amino acid side chains, and deletion
peptides which arise from incomplete couplings [8]. Purification methods typically utilize various
modes of chromatography such as ion exchange chromatography, gel permeation chromatography and
preparative reversed phase high performance liquid chromatography (RP-HPLC) [53]. The amount of
purification required depends on the purity of the crude peptide being purified and the desired purity
of the final peptide product. In sequential SPPS, the amount of purification depends on the number of
amino acids, the more amino acids present, the more purification it requires [29]. RP-HPLC is
predominantly used for the purification of peptides due to its resolution power, demonstrating the
34
ability to separate polypeptides that differ by a single amino acid [54]. The use of RP-HPLC for the
preparative purification of peptides is discussed in further detail in Section 1.7.2.
In the presence of water, peptides can degrade through hydrolysis or other chemical reactions
due to the molecular mobility allowed within a liquid state [55]. As a result, once the desired peptide
purity is achieved in purification, the aqueous peptide solution is typically lyophilised, which is a
more stable way of storing a peptide [55]. Lyophilisation is a process used to preserve a peptide by
freezing the aqueous solution and then applying a pressure to allow the frozen material to sublime
directly from the solid phase to the gas phase [55,56].
1.7 Analytical evaluation of peptides
1.7.1 The use of analytical chemistry for the purification and characterisation of
peptides
Analytical chemistry is the key to peptide synthesis as no synthetic endeavour can be
considered complete until the product has been adequately purified and subjected to a battery of
analytical tests to verify its structure [29]. Analytical chemistry plays an important role in the
preparative purification of peptides as well as the evaluation of the homogeneity and covalent
structure of the peptide [29]. Identity confirmation by nuclear magnetic resonance spectroscopy
(NMR spectroscopy), mass spectrometry (MS) and amino acid analysis (AAA), alongside peptide
content and purity determination by high performance liquid chromatography (HPLC) are all
requirements for analytical evaluation of peptides [57]. Analysis of the counter ion (e.g. acetate,
hydrochloride or trifluoroacetate, etc.) and determination of moisture content are also used to yield
information on peptides, and the results are typically used for the determination of mass balance of the
peptide content [57]. Appearance, solubility, residual solvents by gas chromatography, capillary zone
electrophoresis (CZE) and specific optical rotation are optional tests that can provide additional
information on the peptide [57]. These techniques each have advantages and limitations, such as
HPLC, which can be used for purification and assessment of heterogeneity but does not yield
structural information [29]. Another example is amino acid analysis which accurately quantitates the
amount of peptide and provides molar ratio of amino acid, however it does not distinguish
heterogeneous species, and it is less reliable for some unstable amino acids such as cysteine and the
compositional accuracy decreases as the peptide gets larger [29]. Despite their limitations, each
analytical technique used provides unique information that contributes to the evaluation process [29].
Chromatography is the basis of the main analytical chemistry methods used for the purification,
identification and quantitation of peptides.
35
1.7.2 Reversed phase - High performance liquid chromatography for the evaluation of
peptides
In reversed phase chromatography (RP-HPLC), a non-polar stationary phase is used in
conjunction with polar, largely aqueous mobile phases and this makes up between 70 % and 80 % of
all HPLC applications [58]. This mode of liquid chromatography is so named because the elution
conditions are essentially the reverse of the normal phase chromatography [29]. This mode of HPLC
plays a critical role in analysing and purifying peptides due to its resolution ability [54]. RP-HPLC
has the ability to separate peptides of nearly identical sequences, which may differ by a single amino
acid, for both small peptides and large polypeptides [54].
Reversed phase high performance liquid chromatography (RP-HPLC) involves the separation
of molecules on the basis of hydrophobicity [59]. RP-HPLC separations depend on the hydrophobic
binding of the analyte from the mobile phase to the immobilised hydrophobic n-alkyl ligands attached
to the stationary phase or sorbent as shown in Figure 1.14 [59].
Figure 1.14 Schematic representation of the binding of a peptide to an RP-HPLC silica-based
stationary phase [59]
The mixture containing the analyte is applied to the stationary phase in the presence of
aqueous buffers and the analyte is eluted by the addition of organic solvent to the mobile phase, either
isocratically or by gradient elution [59]. The analyte continuously partitions between the mobile phase
and the hydrophobic stationary phase, however polypeptides are too large to partition in between the
mobile and stationary phase and therefore they absorb to the hydrophobic surface once they enter the
column [54]. Only one part of the polypeptide, known as the ‗hydrophobic foot‘, binds to the
stationary phase [54]. The ‗hydrophobic foot‘ of a polypeptide can vary depending on the amino acid
sequence and conformational properties and therefore, differences in the hydrophobic foot results in
the separation of the polypeptides [54].The polypeptides remain bound to the hydrophobic surface
until the concentration of organic modifier reaches the critical concentration that causes desorption,
where the peptide is eluted from the column [54]. The adsorption/desorption of polypeptides typically
occurs at the top of the column, which means the column length does not impact the separation and
therefore, 5 cm -15 cm columns are typically used [54]. Small peptides desorb faster than
polypeptides and as a result, the column length can impact the separation of smaller peptides and
36
therefore, longer columns of 15 cm -25 cm in length are typically used [54]. The diameter of a RP-
HPLC column is typically 4.6 mm but this is increased for purification by RP-HPLC and reduced if
the LC is coupled with MS [54]. The diameter of the column does not affect peak resolution but it
does affect sample loading, solvent usage and detection sensitivity [54]. Gradient elution is typically
preferred for RP-HPLC because peptides are very sensitive to organic modifier percentage. Isocratic
separation is therefore impracticable for peptide separations because very small differences in the
percentage organic modifier typically result in very significant changes in retention and therefore
gradient elution results in a better separation of peptides and associated impurity peptides [54]. The
analytes are eluted in order of increasing molecular hydrophobicity, with the more polar solutes
eluting first [60,59].
The RP-HPLC packing materials are generally based on micro particulate porous silica which
is chemically modified by a derivitized silane bearing an n-alkyl hydrophobic ligand [59]. The type of
n-alkyl ligand significantly influences the retention time of peptides [59]. The ligand is usually a
linear alphatic hydrocarbon of eighteen (C18), eight (C8) or four (C4) carbons, with other ligands such
as phenyl offering different selectivity [54,59]. Although the effect of the ligand structure is not fully
understood, a number of factors including the ligand chain length, relative hydrophobicity and the
degree of exposure to surface silanols all play a role in the retention process [59]. As a general rule,
retention times of analytes are longer the more carbon atoms the bonded ligand contains [60]. C18
columns are generally preferred for peptides and small proteins less than 5,000 Daltons, whereas
proteins greater than 5,000 Daltons or very hydrophobic polypeptides are best suited for C4 columns
[54]. C8, phenyl and C4 columns offer different hydrophobicity properties and therefore these columns
offer different selectivity for some peptides [54]. Short alkyl groups such as C8 have been
demonstrated to better separate polar samples, whereas long chains are better for non-polar substances
[60]. Most of the surface of a porous packing is contained within the pores and the pore size of a
column determines the ability of the analyte to access the pores [61]. The pore diameter of a column
should exceed the hydrodynamic radius of the analyte by a factor of four or more [61]. For reversed
phase separations of small molecules, column packing with small pores (60-120 Å) is typically used.
For small molecules and peptides, 100-150 Å is typically used and for polypeptides and many
proteins, 200-300 Å column pore size is used [61].
The mobile phase generally consists of mixtures of aqueous buffer solutions with various
water-miscible organic solvents [60]. Aqueous solutions containing trifluoroacetic acid (TFA), formic
acid and ammonium acetate and organic modifiers such as acetonitrile, isopropanol and methanol are
typically used [60]. Water is the weakest mobile phase for RP-HPLC and the more water present, the
slower the elution of the analyte [60]. RP-HPLC is typically the mode of choice for analysis of
peptides at crude stage, analysis during purification and for the analysis of the final API and is by far
the most common technique for the purification of peptides [28].
37
1.7.2.1 The use of RP-HPLC in peptides manufacture
RP-HPLC is used in the purifying and characterising of peptides. Post cleavage of the product
peptide from the solid support, purification is performed on a preparative reversed phase HPLC [8].
Analytical RP-HPLC is then used to analyse the purification fractions [8]. HPLC methods for purity
determination of peptides must enable the separation and determination of the most common
impurities in peptides, such as enantiomers, deletion sequences and products of deamidation or
acetylation [57].
A significant challenge in peptide manufacturing is the lack of harmonized guidelines across
different continents on the level of allowed impurities present in peptide therapeutics [10]. For this
reason, most peptide manufacturers apply a stringent approach on impurities, with limits for
individual, unidentified impurities of less than 0.1 % [10]. Without vigorous characterisation and
evaluation of potential impurities during peptide manufacturing, impurities can be overlooked, often
to reappear at a later stage of the process, potentially leading to recalls or impacts on patient‘s health
and safety [11]. On registration of new drug substances, the actual and potential organic impurities
most likely to arise during the synthesis, purification, and storage need to be evaluated [62]. This
evaluation of potential impurities should be based on sound scientific appraisal of the chemical
reactions involved in the synthesis, impurities associated with raw materials that could contribute to
the impurity profile and possible degradation products [62].
The ability to optimise and control a peptide synthesis process is highly dependent on the
analytical HPLC methods employed [30]. It is critical the correct methods are chosen to evaluate the
peptide and RP-HPLC plays a vital role in this process.
1.7.3 Evolution of ultra-high performance liquid chromatography
As HPLC is the dominant analytical technique in labs worldwide, researchers have put
significant focus on increasing the speed of HPLC, driven by the sheer volume of samples in
laboratories [63]. Faster separation can lead to higher throughput and time savings on analysis and
also in method development [63]. The underlying principle behind the evolution of UHPLC is the
Van Deemter equation, which describes the relationship between linear velocity (flow rate) and height
equivalent to a theoretical plate (HETP).
Dm
uCd
u
BDmAdH
p
p
2
[64]
H represents the height equivalent to a theoretical plate (HETP), dp represents the particle size of the
column packing material, u represents the linear velocity of the mobile phase, Dm outlines the analyte
diffusion coefficient and A-C are constants [64]. A relates to the eddy diffusion, the multiple flow
paths through a column, which is impacted by particle size distribution and uniformity of the packed
bed [65]. B relates to the molecular diffusion and C describes the coefficient of mass transfer, which
38
reflects the time it takes for the analyte to diffuse in and out of the stationary phase [64,65]. C is
directly impacted by the mobile phase velocity due to the fact that higher mobile phase velocities
interfere with the equilibrium between the analyte, mobile phase and stationary phase. As a result, the
longer the path an analyte has to travel within the pores of the stationary phase, the more detrimental
the effect of the mobile phase flow rate will be on the column efficiency [65]. The path a solute has to
travel within the pores of a stationary phase particle can be reduced by using smaller size particles
because smaller particles have shorter diffusion path lengths and, therefore, are less affected by
increases in mobile phase velocity [65]. The Van Deemter equation shows that efficiency varies with
velocity and the optimum velocity occurs at linear velocities that are much lower than those typically
used with particle size of 3.5-5 µm as demonstrated in Figure 1.15 [64].
Figure 1.15 Van Deemter plot demonstrating the effect of particle size on column efficiency (Waters
Corporation) [63]
A decrease in particle size to < 2.5 μm, from the conventional 5 μm particle size, will result in
a significant gain in efficiency [63]. By using smaller particles, peak capacity, which is the number of
peaks that can resolved per unit time of chromatography, and the speed of the separation can be
pushed to new limits [66]. Increased sensitivity will also occur as a result of increased efficiency, due
to the band spreading reduction across the separation process, resulting in sharper chromatographic
peaks [66]. Resolution of a chromatographic separation is proportional to the square root of efficiency
(N), which is inversely proportional to particle size. As a result, decreasing the particle size by a
factor of approximately three (from 5 μm for HPLC to 1.7 μm for UHPLC), results in an increase in
plate count and resolution by the square route of approximately three [67]. A drawback to smaller
particles is higher system pressure, as pressure is inversely proportional to the square root of the
particle size [67]. In order to overcome this problem and take advantage of the increased speed,
39
superior resolution and sensitivity afforded by smaller particles, improved instrumentation and
column technology had to be developed [67].
1.7.3.1 Development of sub-2 μm particles and UHPLC columns
The design and development of sub-2 μm particles was a significant challenge in the
evolution of UHPLC [63]. High efficiency, non-porous 1.5 μm particles were already available but
they suffered from poor retention and poor loading capacity due to low surface area [63]. To maintain
similar retention and loading capacity to HPLC, porous particles that can withstand high pressures
must be used for UHPLC [66]. Silica based particles are used in some UHPLC columns, as they
demonstrate good mechanical strength. However, these columns also have disadvantages in terms of
limited pH range (pH 2.0 – 7.5) and tailing during analysis of basic analytes [63]. Hybrid particles,
which incorporate carbon in the form of methyl groups, were then developed in 2000, which
demonstrated good mechanical strength, high efficiency and they operated at a wide pH range [63].
Waters developed a bridged ethane hybrid (BEH) particle, which involved bridging methyl groups to
the silica, allowing the particle to withstand the pressure required for UHPLC [63]. Fused-core
technology was developed in 2007, which involved superficially porous particles composed of solid
inner core as shown in Figure 1.16 [68]. These fused core particles offer a shorter diffusion path as the
inner core of solid fused silica is impenetrable by analytes, minimising peak broadening [68].
Figure 1.16 Fused-core particle technology [65]
In order to be able to pack the small particles into reproducible and rugged columns, the
packed bed in the column must be uniform and the interior surface of the column hardware must be
smoother to facilitate packing of the small particles into the columns [66,63]. Also, the end frits of the
column must be able to retain the small particles [66]. Particles for sub-2 μm range require extremely
fine frits with porosity of about 0.2 μm, in comparison to frit porosity of 0.5 μm -1 μm which are
typically required for particles in the 3 μm range [69]. A drawback of UHPLC is the occurrence of
viscous heating or frictional heating where friction occurs between different fluid layers inside the
40
column at high flow rates and pressures [70]. Smaller column diameters are a requirement with
UHPLC to avoid the effect of frictional heating [63]. Further improvement on efficiency can be
obtained by increasing column length as plate count is also proportional to column length [67].
Significant developments in sub-2 μm and column technology has been made over the last decade and
currently there is a wide variety of stationary phases packed with sub-2 μm particles, in over 80
chemistries from multiple providers [68].
1.7.3.2 Development of UHPLC instruments
In order to take advantage of the sub-2 μm particles, the HPLC instrumentation needed to be
improved in order to withstand the increased pressures associated with the reduced particle size [66].
A conventional HPLC typically demonstrates a pressure limit of 400 bars but this pressure limit does
not suffice for the use of sub-2 μm particles [64]. For the use of smaller particles, a solvent delivery
system that can deliver solvents at high pressures up to 70 bars and compensate for solvent
compressibility across a range of potential pressures must be used [66]. This system must have an
injection valve that can protect the column from experiencing extreme pressure fluctuations and, low
volume injections, with minimal carryover, are required to accommodate the increased sensitivity
benefits [66]. The detector must also have a high sampling rate to capture enough data points (up to
100 Hz) across the peak to perform accurate and reproducible recognition of the analyte peak and the
detector flow cell must have minimal dispersion to preserve the efficiency of the separation, such as
that observed on UHPLC (Waters, Dublin, Ireland) with a detector flow cell volume of 500 nL
[66,71]. The total system volume must also be reduced, in comparison to HPLC, to ensure the
UHPLC separation is maintained throughout the chromatographic process [66].
In 2004, a UHPLC system that met all of these requirements was made commercially
available from Waters Corporation, known as Acquity UPLC system [63]. This instrument consists
of a binary solvent manager that uses two individual serial flow pumps to deliver a parallel binary
gradient mixed under pressure [67]. The systems also include UV-Vis and PDA detectors with new
electronics and firmware to support high data rates required for UHPLC [67]. The detector cell in the
Acquity systems consist of a light guided flow cell equivalent to an optical fibre and the system has a
1,000 bar pressure limit [67]. Multiple other UHPLC systems have since been developed and UHPLC
technology is now used worldwide, alongside and as a superior replacement of the conventional
HPLC.
1.7.4 Analytical evaluation of coupling reagents during peptide synthesis
During the manufacture of peptides, the synthetic process involves a series of couplings,
washes, de-protections followed by additional washes. It is estimated that most triazole-based
coupling reagents, such as HATU, HBTU, HOBt, PyBOP, PyAOP, and TBTU bind to the solid
41
support during peptide synthesis and are removed during piperidine washes [28]. In the event of a
poor coupling, the triazole-based reagents bind to the free amino acids and these bound triazole-based
reagents are then assumed to be removed by a concentrated base wash, after coupling [28]. So Yeop
Han and Young-Ah Kim stated that a triazine moiety, such as that observed in HCTU, 6-Chloro-
HOBt, TCTU and PyClocK, demonstrates a weak basicity and the by-products and excess coupling
reagents are assumed to be washed out with dilute acid [25]. Fluorous Technologies Incorporated
(Pittsburgh, USA) state that HOBt and DIEA salts are effectively removed by aqueous NaHCO3
wash, whereas Ludmila G. Peeva, et al. used a washing step for the removal of excess reagents via
constant volume diafiltration [72,73]. Alan R. Katritzky et al. stated that the benzotriazole generated
was readily removed by washing the organic extracts with dilute aqueous sodium carbonate during
workup [74]. As outlined above, typically the peptide coupling reagents are assumed to be washed out
during peptide synthesis. If the coupling reagents are still present post synthesis, the purification
process of peptides (involving column chromatography) is assumed to remove the excess coupling
reagents. It is for this reason that very little literature can be found on the analysis of peptides for the
presence of coupling reagents used in the process.
During a development peptide synthesis campaign in Ipsen Manufacturing Ireland LTD, this
assumption was proved to be incorrect. 6-ChloroHOBt was shown to be present all the way through
the synthesis process, throughout the purification fractions and was present in the final, lyophilised
peptide. The presence of 6-ChloroHOBt post-synthesis was a surprising result as the 6-ChloroHOBt
has a high solubility in DMF (>366 mg/mL) and 4 washes of 10 volumes of DMF were performed
during the synthesis, followed by several purification runs. On investigation of the synthetic approach,
increasing the number of DMF washes did not reduce the carryover of 6ChloroHOBt. The purification
strategy was also examined and it was discovered that 6ChloroHOBt was eluting alongside the
peptide, even though they were separated on a HPLC analytical method when standards were
prepared separately. An isocratic hold at the beginning of the purification run allowed the sufficient
separation of the peptide and 6ChloroHOBT to allow removal of the 6-ChloroHOBt to below the
specification in the final API. This problem was suspected to be due to a pH effect in which the
6ChloroHOBt was bound to the peptide. As a result, we can no longer assume the coupling reagents
have been washed out during the synthesis process, regardless of their solubility.
1.7.5 Toxicity of coupling reagents
A genotoxic compound is defined as a compound that has the potential to damage DNA at
any level of exposure and such damage may lead to the development of a tumour [75]. Based on the
safety data sheets (SDS), HOAt, PyBOP, DIU, TBTU and COMU are not identified as human
carcinogens by the International Agency for Research on Cancer (IARC) but there is no data available
for their acute or reproductive toxicity [76 - 80]. This is also the case for HCTU, HBTU, PyBrOP,
42
HOBt, Oxyma pure, and 6-ChloroHOBt [81 - 86]. TMU is also not identified as a human carcinogen
by IARC, however the oral lethal dose50 (LD50) in rats was determined as 794 mg/kg and the dermal
LD50 was determined as 3,160 mg/kg in rabbits [87]. LD50 is defined as the dose that kills half of the
tested population in an animal model, whereas LC50 describes the concentration of a chemical in air
that kills half of the tested population in a given time (usually 4 hours) [88]. LD50 is measured in
milligram (mg) per kilogram (kg) of body weight and LC50 is measured in mg per litre [88]. The
lower the defined amount per kg or per litre, the more toxic the compound, as outlined in Table 1.1.
TMU is characterised as a toxicity rating of 4, slightly toxic, which means approximately 600 ml of
the compound would be the lethal dose for man.
Table 1.1 Toxicology classes - Hodge and Sternar scale [89]
Routes of Administration
Oral LD50 Inhalation LC50 Dermal LD50
Toxicity
Rating
Toxicity
term
(single dose
to rats)
mg/kg
(exposure of rats
for 4 hours) ppm
(single
application to skin
of rabbits) mg/kg
Probable Lethal
Dose for Man
1 Extremely
Toxic
1 or less 10 or less 5 or less 1 grain (a taste,
a drop)
2 Highly
Toxic
1 -50 10-100 5 – 43 4 ml (1 tsp.)
3 Moderately
Toxic
50-500 100-1000 44-340 30 ml (1 fl. oz.)
4 Slightly
Toxic
500-5000 1000-10,000 350-2810 600 ml (1 pint)
5 Practically
Non-toxic
5000-15,000 10,000-100,000 2820-22,590 1 litre (or 1
quart)
6 Relatively
Harmless
15,000 or
more
100,000 22,600 or more 1 litre (or 1
quart)
IARC have not identified TCTU as a human carcinogen but there is also no data for
reproductive toxicity and the oral lethal dose50 (LD50) in rats was determined > 200 mg/kg,
characterising the material as moderately toxic [90]. DIC is also not identified as a human carcinogen
by IARC and an invitro genotoxicity study confirmed this [91]. However, the inhalation lethal
concentration50 (LC50) was determined 4h – 0.105 mg/L (ppm) in rats, characterising the material as
extremely toxic. Unfortunately, there is no toxicity or carcinogenicity available for PyClocK [92].
43
Typically therapeutic peptides are administrated at doses between 50 μg and 50 mg [10]. If a
coupling reagent was present in the peptide product, the quantity would only be present as a very
small fraction of the 50 μg to 50 mg dose administrated to patients and therefore, unless the LD50 and
LC50 results outline the reagent as a 1 or 2 toxicity rating, like DIC, then the reagents shouldn‘t
present an issue in terms of toxicity to patients. However, in the absence of carcinogenicity or toxicity
data, a threshold of toxicological concern (TTC) has been developed to define a common exposure
level for any unstudied chemical that will not pose a risk of significant carcinogenicity or other toxic
effects [75]. This TTC value is estimated as of 1.5 μg/person/day for a lifetime intake and 120
μg/person/day for intake over ≤ 1 month, which is considered to be associated with an acceptable risk
(excess cancer risk of < 1 in 100,000 over a lifetime) for most pharmaceuticals [93]. This is extremely
conservative given that the current lifetime cancer risk in the population is over 1 in 4 [93]. From the
threshold value of 1.5 μg/person/day, a permitted level of the presence of each coupling reagent can
be calculated based on the expected daily dose [75]. For example, if a peptide is administered in a
dose of 20 mg/week, the %w/w of genotoxic impurity allowed for a daily dosage of 2.86 mg is
calculated as follows:
Figure 1.17 Example calculation for determining % w/w of genotoxic impurity allowed for a 20 mg
dose of peptide per week
1.7.6 Ipsen Manufacturing Ireland LTD. approach to the analysis of peptide coupling
reagents
Ipsen Manufacturing Ireland Limited (LTD.), manufacture three active pharmaceutical
ingredients (API), including Lanreotide acetate, Triptorelin acetate and Triptorelin Pamoate, for
commercial supply. These peptides have been produced for several years, with hundreds of batches
manufactured each year. All impurities > 0.1 % have been identified for the commercial peptides and
peptide coupling reagents do not appear to be present in the final API. The analysis of peptide
coupling reagents is performed by HPLC on primary reference standards but is not performed on a
routine basis for every API batch. Ipsen Manufacturing Ireland LTD. also manufactures API for drug
% w/w of genotoxic imp allowed relative to a 20 mg dose per week of Peptide =
1
100
)(/min
)(/.x
mgdayisteredadPeptideofDosage
mgdayimpuritygenotoxicallowedMax
%w/w of genotoxic impurity allowed = wwxmg
mg/%05.0=
1
100
)(86.2
)(0015.0
44
substances and drug products in development for clinical trials and toxicological studies. Typically,
minimal information is known about the manufacture process of development compounds in Phase 1
and 2 clinical trials. As a result, all raw materials used during the manufacturing process are
monitored throughout the manufacturing campaign, including peptide coupling reagents. HPLC
methods are used for the analysis of peptide coupling reagents within Ipsen Manufacturing Ireland
LTD.
1.7.7 Use of HPLC for analysis of coupling reagents:
For the analysis of peptide coupling reagents in the APIs, all the peptide coupling reagents
must be separated sufficiently from the active substance and from each other so that their
concentrations can be reliably measured. Because of the range of polarities between the reagents and
the APIs, multiple HPLC methods of run time greater than 60 minutes are required. This results in
multiple HPLC systems set up for the in-process analysis throughout an API manufacturing
campaign, involving significant amount of resources and time. In order to reduce separation times in
the HPLC method without reducing the quality of the separation requires generating higher resolving
power per unit time [64]. Whilst the resolution between individual analytes in a particular sample may
be increased by improving selectivity or retention, the best general approach to increasing resolving
power is to increase separating efficiency, such as that done in ultra-high performance liquid
chromatography (UHPLC) [64].
1.8 Aim of the thesis
The aim of this thesis was to develop a rapid liquid chromatography method for the in-process
determination of fourteen peptide coupling reagents used in peptide synthesis. This method was
required because studies at Ipsen Manufacturing Ireland LTD. have revealed that some peptide
coupling reagents may in fact not be fully removed from the peptide product during peptide
manufacture. The novelty of this body of work lies in the fact that the simultaneous chromatographic
separation of these reagents has heretofore not been demonstrated in the literature. It is likely that this
is due to the erroneous assumptions made in the peptide synthesis industry regarding the clearance of
these reagents during peptide manufacturing, as described in Section 1.7.4. The analytes chosen were
either used in the manufacture of some commercial peptides at Ipsen Manufacture Ireland LTD., or
were under investigation for the manufacture of peptides in development at the time of this study.
This thesis involves the selection of a commercially available stationary phase and a mobile phase that
is compatible with mass spectrometry to evaluate peptide coupling reagents in peptides provided by
Ipsen Manufacturing Ireland LTD. This thesis is divided into two separate chapters. Chapter 2 deals
with the development of a reversed phase HPLC assay for the selected reagents and it involves
stationary phase selection and optimisation of mobile phase composition. Chapter 3 then goes on to
describe the validation of the analytical method using standard method performance criteria such as
45
sensitivity, linearity, robustness, etc. Although UV detection was used for the method described in
this thesis, nevertheless, a mobile phase system which was compatible with mass spectrometric
detection was developed in order to maximise the potential utility of the method.
46
_________________________________________________________________________
2. Chapter 2
Development of a UHPLC method for the analysis of peptide coupling reagents, additives
and associated by-products during peptide synthesis
__________________________________________________________________________
47
2.1 Introduction
The determination of peptide coupling reagents, additives and associated by-products is
important during peptide synthesis to ensure the concentration of these products are below the
threshold of toxicological concern in the final peptide. Several publications have dealt with the
development of these compounds as coupling reagents but none specifically focus on the detection of
these compounds in the final peptide. This is due to the assumption that they are washed out during
peptide synthesis as discussed in Section 1.7.4, however research at Ipsen Manufacturing Ireland
LTD. has proven this assumption to be incorrect.
TMU, HOBt, HCTU, HBTU, 6-ChloroHOBt, TBTU, PyClocK, Oxyma Pure COMU, DIU,
DIC, PyBOP, PyBrOP, and TCTU are peptide coupling reagents, additives and associated by-
products commonly associated with peptide synthesis. In order to monitor these products during a
peptide synthesis campaign, it was necessary to develop a quantitative detection method. This method
will subsequently be used in Ipsen Manufacturing Ireland LTD., for evaluating all stages of the
manufacture of development peptides to ensure the removal of the compounds.
Historically in Ipsen Manufacturing Ireland LTD., HPLC was previously the method of
choice for the analysis of peptide coupling reagents in API samples, but due to the wide range of
polarities between the reagents and the APIs, multiple HPLC methods of run time greater than 60
minutes were in place. This resulted in multiple HPLC systems set up for in-process analysis
throughout a peptide manufacturing campaign, involving significant amount of resources and time. In
order to reduce separation times in a HPLC method without reducing the quality of the separation, a
higher resolving power is required per unit time and the best general approach to increasing resolving
power is to increase separation efficiency, by decreasing particle size and using ultra-high
performance liquid chromatography (UHPLC), as discussed in Chapter 1, Section 1.7.3. UHPLC is a
relatively new mode of separation science which builds upon well-established principles of liquid
chromatography, using sub-2μm porous particles. These particles operate at elevated mobile phase
linear velocities to produce rapid separations with increased sensitivity and resolution.
The work presented in this chapter involves the development of a rapid liquid
chromatography method for the in-process determination of fourteen peptide coupling reagents used
in peptide synthesis. The analytes chosen are either used in the manufacture of some commercial
peptides or are under investigation for the manufacture of peptides in development in Ipsen
Manufacturing Ireland LTD. A number of column technologies and mobile phases were evaluated for
the separation of the analytes. Therefore the aim of this chapter is to select a commercially available
stationary phase with a mobile phase that is compatible with mass spectrometry to evaluate peptide
coupling reagents in peptides provided by Ipsen Manufacturing Ireland LTD., in a run time of less
than 30 minutes.
48
2.2 Experimental
The study was first initiated with a well-defined set of peptide synthesis reagents, additives and
associated by-products which were identified as being of specific interest to Ipsen Manufacturing
Ireland LTD. The initial set of compounds included Peptide 1, TMU, HOAt, HOBt, HCTU, HBTU, 6-
ChloroHOBt, TBTU, PyClocK, Oxyma Pure and COMU. Therefore, for the most part, the following
experimental section is written in chronological order and the individual experiments were conducted
using the range of materials previously listed (and referred to hereafter as ‗Sample set A‘).
Midway through the method development, a further five reagents were added to the set of
materials under investigation in order to widen the scope of the method. These additional five
reagents were identified as further potential materials that could be used by Ipsen Manufacturing
Ireland LTD., in the future and so their inclusion in the study (albeit midway through method
development) represents an effort to ‗future-proof‘ the method. As a result, the final method would be
applicable for the use of a much broader range of peptide coupling reagents, additives and associated
by-products as dictated by emerging future trends in peptide synthesis in Ipsen Manufacturing Ireland
LTD.
In some cases, the inclusion of the new reagents to the sample set under study necessitated that
previous experiments be revisited and further optimised to reflect the new sample set (referred to
hereafter as ‗Sample set B‘) and comprising of the reagents from ‗Sample set A‘ (as listed above) and
also DIU, DIC, PyBop, PyBrOP, and TCTU. For the sake of clarity, Table 2.1 sets out the
chronological order of method development experiments, clearly indicating which sample set was
under investigation i.e. ‗Sample set A‘ or the more comprehensive ‗Sample set B‘. This table is
therefore intended as a reference guide to assist the reader.
49
Table 2.1 Chronology of method development indicating materials under investigation
Section Experiment Sample set
2.2.3 Solubility studies B
2.2.4 Determination of optimum detection wavelength B
2.2.5 Evaluation of columns and mobile phase systems A
2.2.6 Design of experiments A
2.2.7 Initial evaluation of optimum buffer pH and column temperature A
2.2.8 Re-optimisation of optimum pH using 10 mM ammonium formate A
2.2.9 Evaluation of flow rate for optimum separation A
2.2.10 Re-optimisation of column temperature B
2.2.11 Evaluation of final percentage acetonitrile required for the gradient Peptide 1
2.2.12 Re-optimisation of optimum buffer concentration B
2.2.13 Evaluation of chromatographic gradient profiles B Note:
Sample set A - Peptide 1, TMU, HOAt, HOBt, HCTU, HBTU, 6-ChloroHOBt, TBTU, PyClocK, Oxyma Pure and COMU.
Sample set B - Peptide 1, TMU, HOAt, HOBt, HCTU, HBTU, 6-ChloroHOBt, TBTU, PyClocK, Oxyma Pure, COMU, DIU, DIC, PyBop, PyBrOP, and TCTU.
2.2.1 Reagents and standards
HPLC grade acetonitrile (J.T Baker) and LC-MS grade acetonitrile (Ocon Chemicals) were
purchased from Sigma Aldrich (Dublin, Ireland). Methanol was obtained from Labscan (Dublin,
Ireland). Purified water was obtained from a Millipore Milli-Q water (H2O) purification system (EMD
Millipore Corporation, MA, USA). HPLC grade ammonium formate, acetic acid, ammonium acetate,
formic acid, phosphoric acid, sodium phosphate, dimethylformamide (DMF), sodium hydroxide,
trifluoroacetic acid (TFA) and ammonium hydroxide were all purchased from VWR (Dublin, Ireland).
All active pharmaceutical peptides and diisopropylurea were obtained from Ipsen Manufacturing
Ireland LTD. Tetramethylurea (Fluka), diisopropylcarbodiimide (99 %, Aldrich), TBTU (Aldrich),
HOBt (Aldrich) and HBTU (Aldrich) were purchased from Sigma Aldrich (Dublin, Ireland). PyBOP,
HCTU, PyClocK and PyBrOP were all Novabiochem products and were obtained from Merck
(Darmstadt, Germany). COMU, Oxyma pure and TCTU were all purchased from Luxembourg
Biotechnologies Ltd. (Rehovet, Israel). 6-ChloroHOBt was obtained from Apollo Scientific Ltd.
(Cheshire, United Kingdom) and HOAt was obtained from Acros Organics (Geel, Belgium).
2.2.2 Instrumentation
Chromatographic separations were carried out on numerous LC instruments to maximise lab
productivity. Chromatographic separations were performed on a Waters H-Class (quaternary pump)
UPLC and a Waters Acquity (Binary pump) UPLC, equipped with a TUV detector and FTN sample
manager (Waters, Dublin, Ireland). A Waters 2695 separations module HPLC, equipped with a PDA
50
detector, was also used (Waters, Dublin, Ireland). The data was acquired via Waters Empower 2
software. Weighing was performed on a Mettler Toledo XP205 analytical balance and a Mettler
Toledo XP6 microbalance (Mason Technology, Dublin, Ireland). The pH meter used was a Mettler
Toledo SevenMulti pH meter (VWR, Dublin, Ireland).
2.2.3 Solubility studies
Solubility studies were performed to determine the optimum solvent to dissolve all peptide
coupling reagents, additives and associated by-products. The solubility studies were carried out in
water (H2O), 0.1 M acetic acid (AcOH), methanol (MeOH) and acetonitrile (ACN). Solubility
determination was performed by weighing 0.1 g of material into a 10 mL volumetric flask and adding
increasing volume increments (100 µL, 1000 µL, 3 mL and 10 mL) of solvent. If samples did not
dissolve after the addition of 10 mL of solvent, then the diluent volume was increased to 100 mL with
6 hours of sonication, or if necessary, 1000 mL of diluent with 24 hours of sonication. In all cases,
sonication and visual inspection of sample solution was performed at ambient temperature.
2.2.4 Determination of optimum detection wavelength
Each reagent was evaluated between 210 nm and 400 nm on a photodiode array detector to
determine the optimum detection wavelength for liquid chromatography (LC) analysis. This was
performed by dissolving each reagent in ‗Sample set A‘ in the optimum solvent, determined as per
Section 2.2.4, and performing analysis on a Waters Acquity system with a PDA detector using a BEH
C18 100 mm x 2.1 mm column. A multi-step gradient was employed as detailed in Table A1 in
Appendix 1.
Each additional coupling reagent in ‗Sample set B‘ that is not in ‗Sample set A‘ was
evaluated between 210 nm and 400 nm on a photodiode array to determine the optimum detection
wavelength for LC analysis. This was performed by dissolving each reagent in optimum solvent and
analysing on a Waters 2695 HPLC system with a PDA detector, using an YMC-ODS-AM 250 mm x
4.6 mm x 2.1 mm column as per the gradient detailed in Table A2 in Appendix 1.
2.2.5 Evaluation of columns and mobile phase systems
Using the optimum sample diluent of 80 % H2O, 10 % MeOH and 10 % ACN, and the
optimum detection wavelength of 220 nm, a mix containing ‗Sample set A‘ was analysed using
multiple different mobile phase systems outlined in Table 2.2 and a series of columns outlined in
Table 2.4. For columns 2, 9, 11 and 13, each reagent from ‗Sample set A‘ was individually analysed
on each mobile phase system in addition to the mixture of reagents analysed on all other columns.
51
Table 2.2 Mobile phase systems under evaluation
Mobile phase
system number Mobile phase A Mobile phase B
A 0.1 % TFA 0.08 % TFA in ACN
B 0.1 % TFA 0.08 % TFA in MeOH
C 0.1 % Formic acid 0.08 % Formic acid in ACN
D 0.1 % Formic acid 0.08 % Formic acid in MeOH
E 10 mM Ammonium acetate pH 4.0 Acetonitrile
F 10 mM Ammonium acetate pH 4.0 Methanol
G 10 mM Ammonium formate pH 3.0 Acetonitrile
H 10 mM Ammonium formate pH 3.0 Methanol
I 10 mM Sodium phosphate pH 2.0 Acetonitrile
J 10 mM Sodium phosphate pH 2.0 Methanol
K 10 mM Sodium phosphate pH 7.0 Acetonitrile
L 10 mM Sodium phosphate pH 7.0 Methanol
Table 2.3 outlines the multi-step gradient applied to each column. A detection wavelength of 220 nm
and an injection volume of 5 μL were employed for all experiments.
Table 2.3 Comparison table for columns under investigation and the corresponding gradient profiles
Columns
Gradient profile used
(Appendix 1)
1,2,3,4 A3
5,6 A4
7,8,9 A5
10,11 A6
12 A7
13,14 A8
15 A9
16 A10
17 A11
Note: All subsequent sections of the Experimental were analysed on Column 15 (YMC Triart 100
mm x 2.0 mm, 1.9 µm) using the optimum diluent of 80 % H2O, 10 % MeOH and 10 % ACN, the
optimum detection wavelength of 220 nm and an injection volume of 5 μL, unless otherwise
specified. All chromatograms were evaluated based on standard chromatographic criteria.
52
Table 2.4 Columns under investigation (including detailed physical specifications)
Column
number Column Manufacturer Phase
Particle size
(µm) Dimensions Pore size Ligand type pH range Temp limits
Surface
area
Carbon
load Capping
1 Acquity HSS C18
[94] Waters HSS 1.8 µm
100 x 2.1
mm 100Å
Trifunctional
C18 1-8 Max 45 °C 230 m2/g 15 % End capped
2 Acquity HSS T3
[94] Waters HSS 1.8 µm
100 x 2.1 mm
100 Å Trifunctional
C18 2-8 Max 45 °C 230 m2/g 11 % End capped
3 Agilent Zebra SB
C18 [95] Agilent Zorbax SB 1.8 µm
100 x 2.1
mm 80 Å C18 1-8 Max 90 °C 180 m2/g 10 %
Non-end
capped
4 Acquity HSS C18
SB [94] Waters HSS 1.8 µm
100 x 2.1
mm 100 Å
Trifunctional
C18 2-8 Max 45 °C 185 m2/g 8 %
Non-end
capped
5 Acquity BEH300
C4 [95] Waters BEH 1.7 µm
100 x 2.1
mm 300 Å
Monofunctional
C4 1-10
Low pH=80 °C
High pH=60 °C 185 m2/g 8 %
Non-end
capped
6 Acquity BEH
Phenyl [94] Waters BEH 1.7 µm
100 x 2.1
mm 130 Å
Trifunctional
C6 Phenyl 2-11
Low pH=80 °C
High pH=60 °C 185 m2/g 15 % End capped
7
Acquity BEH C18 Shield [94]
Waters BEH 1.7 µm 50 x 2.1 mm 130 Å
Monofunctional
embedded polar
group C18
1-12 Low pH=50 °C High pH=45 °C
230 m2/g 17 % End capped
8 Acquity BEH C18
[94]
Waters BEH 1.7 µm 50 x 2.1 mm 130 Å Trifunctional
C18 1-12
Low pH=80 °C
High pH=60 °C 185 m2/g 18 % End capped
9 Phenomenex Kinetex [96]
Phenomenex C18 1.7 µm 50 x 2.1mm 100 Å C18 1.5-10 60 °C 200 m²/g 12 % End capped
10 Agilent Eclipse Plus
C18 [95] Agilent Eclipse plus 1.8 µm 50 x 4.6 mm 95 Å C18 2-9 Max 60 °C 160 m²/g 9 % Double
11 Agilent Eclipse Plus
C8 [95] Agilent Eclipse plus 1.8 µm 50 x 4.6 mm 95 Å C8 2-9 Max 60 °C 160 m²/g 7 % Double
12 Halo C18 [65]
Advanced
Materials technology
C18 2.7 µm (1.7μm
solid core) 50 x 2.1mm 90 Å C18 2-9 Max 90 °C 150 m²/g 10 % End capped
13
YMC Ultra HT
Hydrosphere C18
[97]
YMC
YMC
Hydrosphere
C18
2 µm 50 x 3mm 120 Å C18 2-8 Max 50 °C 330 m²/g 12 % End capped
14 YMC Ultra HT Pro
C18 [97] YMC YMC Pro C18 2 µm 50 x 3mm 120 Å C18 2-8 Max 60 °C 330 m²/g 17 % End capped
15 YMC Triart C18
[98] YMC
YMC Triart
C18 1.9 µm
100 x
2.0mm 120 Å C18 2-8
Low pH=70 °C
High pH=50 °C 330 m²/g 20 %
Multi staged
hybrid groups
16 Acclaim RSLC 120
C18 [99] Dionex C18 2.2 µm
100 x
2.1mm 120 Å C18 2-8 Max 60 °C 300 m²/g 18 % End capped
17 Hypersil gold [100] Thermo C18 1.9 µm 100 x
2.1mm 175 Å C18 1-11 Max 60 °C 220 m²/g 10 % End capped
53
2.2.6 Design of experiments
After the optimum stationary phase and mobile phase were selected, further optimisation was
performed on the composition of the mobile phase, pH of the mobile phase, system flow rate, column
temperature and gradient change. Modde 9 software was used to compile an experimental design
space where all of these parameters were varied at the same time. Evaluation of chromatograms was
performed for each of the 19 experiments outlined in Table 2.6 and in addition, each reagent was also
individually injected for experiment N11 and N15. Table 2.5 outlines the multi-step gradient applied
to each experiment.
Table 2.5 Design of experiments and corresponding gradient profiles
Experiments
Gradient profile
used (Appendix 1)
N1, N4, N6, N7, N10, N11, N13 and N16 A12
N2, N3, N5, N8, N9, N12, N14 and N15 A13
N17, N18 and N19 A14
Table 2.6 Parameters evaluated during design of experiments for mobile phase optimisation
Exp no. pH
Concentration of
buffer (mM) *
Flow rate
(mL/min)
Temp
(°C)
Mobile phase B
change/min (%)
N1 3.8 5 0.3 20 1.2
N2 9.2 5 0.3 20 0.2
N3 3.8 50 0.3 20 0.2
N4 9.2 50 0.3 20 1.2
N5 3.8 5 0.5 20 0.2
N6 9.2 5 0.5 20 1.2
N7 3.8 50 0.5 20 1.2
N8 9.2 50 0.5 20 0.2
N9 3.8 5 0.3 50 0.2
N10 9.2 5 0.3 50 1.2
N11 3.8 50 0.3 50 1.2
N12 9.2 50 0.3 50 0.2
N13 3.8 5 0.5 50 1.2
N14 9.2 5 0.5 50 0.2
N15 3.8 50 0.5 50 0.2
N16 9.2 50 0.5 50 1.2
N17 3.8 27.5 0.4 35 0.7
N18 3.8 27.5 0.4 35 0.7
N19 3.8 27.5 0.4 35 0.7 *Buffer = Ammonium formate
54
2.2.7 Initial evaluation of optimum buffer pH and column temperature
Further optimisation was performed with 10 mM ammonium formate pH 2.8, 3.8 and 4.8, each at
column temperatures of 25 °C, 35 °C and 45 °C using the gradient detailed in Table A15 in Appendix
1. Another experiment was then performed using 10 mM ammonium formate pH 4.8 with a range of
column temperatures from 10 °C to 50 °C using the same multi-step gradient detailed in Table A15 in
Appendix 1.
2.2.8 Re-optimisation of buffer pH using 10 mM ammonium formate
Following the addition of more peptide coupling reagents and associated by-products to the
study as explained on page 2, the optimum pH range was re-evaluated for the ammonium formate
buffer at a range of 2.8 to 4.8 (2.8, 2.9, 3.0, 3.1, 3.2, 3.3, 3.8, 4.3 and 4.8) . This was carried out by
dissolving each reagent in ‗Sample set B‘ in the optimum diluent at a concentration of 0.5 mg/mL and
analysing using the multi-step gradient detailed in Table A15 in Appendix 1.
2.2.9 Evaluation of flow rate for optimum separation
After the optimum ammonium formate concentration and pH were selected, further
optimisation was performed with a range of flow rates from 0.25 mL/min, 0.30 mL/min and 0.35
mL/min using the gradient detailed in Table A16 in Appendix 1. An injection volume of 10 μL and a
column temperature of 25 ºC were also employed.
2.2.10 Re-optimisation of column temperature
Following the addition of new peptide reagents and the change in optimum pH of ammonium
formate, further optimisation was performed with a range of column temperatures from 10 °C to 45
°C, at 5 °C intervals, using the gradient detailed in Table A16 in Appendix 1.
2.2.11 Evaluation of final percentage acetonitrile required for the gradient
An investigation was performed to determine the effect of percentage acetonitrile on the last
eluting peak, PyBrOP. This was carried out by dissolving PyBrOP at a concentration of 0.5 mg/mL
and analysing on three different gradients with varying final percentages of the acetonitrile. Three
multi-step gradients were employed using 10 mM ammonium formate pH 3.3 as mobile phase A as
detailed in Table A17 (experiment 1), Table A18 (experiment 2) and Table A19 (experiment 3) in
Appendix 1.
55
2.2.12 Re-evaluation of optimum buffer concentration
Following the addition of new peptide reagents and the change in optimum pH of ammonium
formate, further optimisation was performed on the concentration of ammonium formate in mobile
phase A. This was performed with a range of concentrations of ammonium formate from 5 mM to 40
mM (in 5 mM intervals). The multi-step gradient detailed in Table A20 (Appendix 1) was employed
for each concentration of ammonium formate at pH 3.3.
2.2.13 Final optimisation of chromatographic gradient profiles
An evaluation of the gradient profile and flow rate for the method was carried out by
analysing ‗Sample set B‘ on each gradient detailed in Appendix 2.
2.3 Results and discussion
2.3.1 Assessment of samples for analysis
HPLC method development typically follows a systematic strategy that includes a series of
steps outlined in Figure 2.1.
56
1. Information on sample,
define separation goals
2. Need for special HPLC
procedure, sample,
pretreatment, etc.?
3. Choose detector and
settings
4. Choose LC method:
Preliminary run, estimate
best separation conditions
5. Optimize separation
conditions
6. Check for problems or
requirement for special
procedure
7a. Recover purified
material
7b. Quantitative
calibration
7c. Qualitative
method
8. Validate method for
release to routine
laboratory
Figure 2.1 HPLC method development schematic
Sample information was required in order to define the method development goal and strategy [94].
This information included the chemical structure, molecular weight, UV spectra, solubility of each of
the compounds and also the number of compounds present in the sample [8]. It should be noted that
this data was generated for the reagents defined earlier as ‗Sample set A‘. Similar data for ‗Sample set
B‘, which includes the additional reagents added to the study, is presented later in this chapter to more
accurately reflect the chronology of the method development.
2.3.1.1 Assessment of analyte chemical structure
The chemical structure of each peptide coupling reagent, additive and associated degradant is outlined
in Table 2.7.
57
Table 2.7 Chemical structure of all peptide coupling reagents, additives and by-products
Compound Structure Detail
HOBt [31,84]
Molecular weight: 135.12g mol-1
HOAt [101,76]
Molecular weight: 136.11g mol-1
6-ChloroHOBt
[31,86]
Molecular weight: 169.57g mol-1
HCTU [48,81]
Molecular weight: 413.69g mol-1
Oxyma pure
[47,85]
Molecular weight: 142.11g mol-1
TBTU [31,79]
Molecular weight: 321.08g mol-1
PyClocK
[46,92]
Molecular weight: 554.84g mol-1
HBTU [31,82]
Molecular weight: 379.3g mol-1
COMU [16,80]
Molecular weight: 428.27g mol-1
TMU [87,102]
Molecular weight: 116.16g mol-1
58
2.3.1.2 Solubility determination
The solubility study was carried out in H2O, 0.1 M acetic acid (AcOH), methanol (MeOH)
and acetonitrile (ACN) as outlined in Section 2.2.3. High organic diluents injected onto a highly
aqueous mobile phase can result in the splitting of peaks on the chromatogram and as a result, the
ideal diluent would be composed of a small amount of organic solvent. The US Pharmacopeia
outlines that the approximate solubility of a substance, evaluated at 20 °C, is described by one of the
terms described in Table 2.8.
Table 2.8 USP solubility definitions [103]
Definition Volume of solvent required per 1g of solute
Very soluble Less than 1 mL of solvent needed to dissolve 1 g solute
Freely soluble 1 mL-10 mL of solvent needed to dissolve 1 g solute
Soluble 10 mL-30 mL of solvent needed to dissolve 1 g solute
Sparingly soluble 30 mL-100 mL of solvent needed to dissolve 1 g solute
Slightly soluble 100 mL-1000 mL of solvent needed to dissolve 1 g solute
Very slightly soluble 1000 mL-10,000 mL of solvent needed to dissolve 1 g solute
Practically insoluble More than 10,000 mL of solvent needed to dissolve 1 g solute
The reagents in ‗Sample set A‘ were all classified according to the USP solubility definition
and the optimum diluent for each reagent is underlined Table 2.9.
The optimum diluent was determined as the solvent composition that dissolved the highest
concentration of each of the reagents. The optimum diluent was different for some of the reagents and
several reagents demonstrate poor solubility in aqueous solutions. As a result, the order of addition of
solvent is important and there was a requirement to initially add the optimum diluent to fully dissolve
the reagents, followed by a dilution with an aqueous solution. The optimum solvent was determined
as 80/10/10 H2O/ACN/MeOH and the order of addition required was determined as per Table 2.10.
59
Table 2.9 Solubility of coupling reagents, additives and associated by-products.
Compound Solvent
USP solubility
description
Approx solubility
concentration
HCTU 0.1 M AcOH Slightly soluble 1 mg/mL
H2O Slightly soluble 1 mg/mL
MeOH Slightly soluble 1 mg/mL
ACN Freely soluble 100 mg/mL
HBTU 0.1 M AcOH Slightly soluble 1 mg/mL
H2O Slightly soluble 1 mg/mL
MeOH Slightly soluble 1 mg/mL
ACN Freely soluble 100 mg/mL
HOBt 0.1 M AcOH Slightly soluble 1 mg/mL
H2O Slightly soluble 1 mg/mL
MeOH Freely soluble 100 mg/mL
ACN Sparingly soluble 10 mg/mL
HOAt 0.1 M AcOH Slightly soluble 1 mg/mL
H2O Slightly soluble 1 mg/mL
MeOH Soluble 33.33 mg/mL
ACN Slightly soluble 1 mg/mL
6-ChloroHOBt 0.1 M AcOH Slightly soluble 1 mg/mL
H2O Very slightly soluble 0.1 mg/mL
MeOH Freely soluble 33.33 mg/mL
ACN Slightly soluble 1 mg/mL
Oxyma Pure 0.1 M AcOH Soluble 10 mg/mL
H2O Soluble 10 mg/mL
MeOH Very soluble 1000 mg/mL
ACN Freely soluble 100 mg/mL
COMU 0.1 M AcOH Slightly soluble 1 mg/mL
H2O Slightly soluble 1 mg/mL
MeOH Soluble 10 mg/mL
ACN Freely soluble 33.33 mg/mL
PyClocK 0.1 M AcOH Very slightly soluble 0.1 mg/mL
H2O Very slightly soluble 0.1 mg/mL
MeOH Slightly soluble 1 mg/mL
ACN Freely soluble 100 mg/mL
TBTU 0.1 M AcOH Freely soluble 33.33 mg/mL
H2O Soluble 10 mg/mL
MeOH Soluble 10 mg/mL
CAN Freely soluble 100 mg/mL
60
Table 2.10 Order of diluent addition for dissolving analytes under investigation.
Product
Initial
diluent Second diluent
Third
diluent
HCTU ACN MeOH H2O
HBTU ACN MeOH H2O
HOBt MeOH ACN H2O
HOAt MeOH ACN H2O
6ChloroHOBt MeOH ACN H2O
Oxyma Pure ACN MeOH H2O
COMU ACN MeOH H2O
PyClocK ACN MeOH H2O
TBTU ACN MeOH H2O
2.3.1.1 Determination of optimum detection wavelength for „Sample set A‟
The type of detector used for the detection of analytes impacts the relative response of sample
components in terms of sensitivity, selectivity and baseline noise. Detection affects assay sensitivity
via the signal to noise ratio (S/N). As a result, better sensitivity can be achieved by increasing the S/N
ratio. Determining the optimum wavelength will maximise the signal for each of the analytes. The
wavelength chosen for detection must provide acceptable absorbance by the various analytes in the
sample, combined with acceptable light transmittance by the mobile phase [61]. Typically, HPLC
method development is carried out with an ultraviolet (UV) detector, however alternative detectors
may be required if analytes have minimal or no UV absorbance, analyte concentrations are too low for
UV detection or sample interferences are present [61]. Each reagent was therefore evaluated between
210 nm and 400 nm on a photodiode array detector to determine the optimum detection wavelength,
as shown in Figure 2.2.
The UV absorbance profiles of the mobile phases that were investigated during the method
development were accessed as outlined in Table 2.11. Water is effectively non-absorbing above 180
nm, so this mobile phase component can be ignored [61]. The mobile phase must transmit sufficiently
at the wavelength used for detection as baseline noise has been demonstrated to increase significantly
when absorbance (AU) of the mobile phase is greater than 0.7 [61]. Less pure solvents can
demonstrate a higher UV absorbance and as a result, all reagents used were of HPLC grade or higher
[60].
61
Figure 2.2: PDA profile of reagents in „Sample set A‟. The red dotted line represents the optimum
wavelength.
62
Table 2.11 Absorbance (AU) of mobile phase components at selected wavelengths (nm) [61,104,105]
Absorbance (AU) at wavelength specified (nm)
Mobile phase
component 200 205 210 215 220 230 240 250 260 280
Acetonitrile 0.05 0.03 0.02 0.01 0.01 <0.01 - - - -
Methanol 2.06 1.00 0.53 0.37 0.24 0.11 0.05 0.02 <0.01 -
0.1 % TFA 1.20 0.78 0.54 0.34 0.20 0.06 0.02 <0.01 - -
0.1 % TFA in
acetonitrile 0.29 0.33 0.37 0.38 0.37 0.25 0.12 0.04 0.01 <0.01
10 mM Ammonium
acetate 1.88 0.94 0.53 0.29 0.15 0.02 <0.01 0.02 - -
100 mM Sodium
phosphate pH 6.8 1.99 0.75 0.19 0.06 0.02 0.01 0.01 0.01 0.01 <0.01
Ammonium
formate UV cut-off 210 nm (AU > 0.5) 0.05 0.04
0.1 % Formic acid
1.00 0.50 0.10 0.02 - 0.01
0.1 % Formic acid
in acetonitrile
1.00 0.50 0.10 0.05 - 0.05
A wavelength of 220 nm was selected based on results outlined in Figure 2.3. At this wavelength, all
components will be clearly visible with minimal interference from mobile phase composition. Formic
acid demonstrates a high absorbance for at ≤ 220 nm, however this was partially negated by the
addition of formic acid in both mobile phase A (0.1 % formic acid) and mobile phase B (0.1 % formic
acid in acetonitrile) [104].
2.3.1.2 Evaluation of multiple columns and mobile phase systems prior to detailed method
development.
Reverse phase chromatography (RPC) is typically the first choice for most regular samples
with a vast selection of efficient, stable and reproducible columns [61]. RPC separations are typically
carried out with silica-based, bonded-phase columns and the sample retention mainly depends on
three characteristics on a column: bonded ligand type, concentration of bonded phase and column
surface area [61]. Further effects upon retention and/or peak shape are due to non-specific interactions
with the silica substrate (silanols), which can be reduced to some extent by end capping or by addition
of mobile phase additives‘. Variations to bonded ligand type can result in changes to selectivity of
analytes and therefore several types of columns were chosen to be evaluated during the method
development. C18 (octyldecylsilane, ODS) columns are particularly useful for the separation of
peptides less than 2,000 Daltons and as a result, a lot of the columns chosen for the evaluation in this
study were C18 [106]. The choice of the pore size is determined by the molecular weight of the
component being analysed and based on Table 2.7, all of the analytes under investigation have a small
molecular weight [106]. For the reversed phase separation of small molecules, column packing with
63
small pores (60-120 Å) is typically used [106]. For small molecules and peptides, 100-150 Å is
typically used and for polypeptides and many proteins, 200-300 Å column pore size is used [106].
Therefore, most of the columns chosen for the method development investigation had pore sizes of 80
to 130 Å, with two higher pore size columns included to evaluate the effect of column pore size on the
separation of the analytes. This is because wide pore columns can also separate peptides well and
often result in different selectivity and resolution [31].
Each column was assessed using the Product Quality Research Institute (PQRI) approach by
United States Pharmacopeia (USP) to ensure they were not equivalent. The PQRI approach provides
characterisation of every reversed phase column in terms of hydrophobicity (H), steric interaction
(S*), hydrogen-bond acidity (A) and basicity (B), and relative silanol ionization or cation-exchange
capacity (C) [103]. Column hydrophobicity (H) increases with an increase in total carbon. H also
increases for small-pore columns due to the compression of the ends of the alkyl chains. Column
steric interactions (S*) increase as the bonded phase becomes more crowded, such as with increased
chain length or narrow-pore packing‘s. Column hydrogen-bond acidity (A), due to non-ionized
silanols, increases with column acidity. Column hydrogen-bond basicity (B) arises from various
functional groups within the bonded ligand and in general, columns with high B values preferentially
retain acidic compounds. Overall, column hydrophobicity has only a minor effect on column
selectivity, while S*, A and B have a significant effect on column selectivity. Relative silanol
ionization or cation-exchange capacity (C) is dependent on mobile phase pH and therefore the USP
program allows a choice of pH = 2.8 (low) or 7.0 (high), whichever value is closest to the actual
mobile phase pH and also allows the assessment of acidic and basic analytes [103].
Using the PQRI parameters, each column was therefore compared and their similarities are
indicated by an F value as shown in Table 2.12. Columns which have values of F ≤ 3 are very likely
to give an equivalent and acceptable separation for any sample. The larger the F value, the greater the
difference between the columns [103]. This was used to ensure the columns chosen for method
development would demonstrate different selectivity. The Acquity BEH 300 C4 and Acquity BEH
C18 have not been classified by UPS-PQRI and therefore no F value could be determined. All F
values were determined as > 3 at pH 2.8 for acidic and basic analytes, with the exception of the Halo
C18 and the Agilent Zorbax Extend C18, with an F value of 2.53 and the comparison of Agilent
Zorbax Eclipse Plus C18 and Phenomenex Kinetix, which demonstrated an F value of 2.65. These
columns were then compared at pH 7.0 and the F value for Agilent Zorbax Eclipse Plus C18 and
Phenomenex Kinetix was subsequently determined as 9.06. However, the F value between Halo C18
and the Agilent Zorbax Extend C18 was 2.39 and as a result, the Agilent Zorbax Extend C18 column
was removed from the method development investigation.
64
Table 2.12 Comparison of columns by PQRI approach at pH 2.8 for acidic and basic compounds
65
To ensure that all columns were evaluated equally, a gradient for each column was calculated to
account for differences in particle size, column length and diameter. For this, a gradient of 0.9 % B
change per minute, for a 100 mm (length) x 2.1 mm (diameter) and 1.7 µm (particle size), a flow rate
of 0.4 mL/min, was chosen as the standard conditions. The gradient for every other column was then
determined manually using the calculations outlined below [108].
1. To determine flow rate with target column:
2. To determine the gradient duration for each step in the original gradient
Gradient volume = Flow rate x Time
Column volume = π x r2 x Length of column
3. To calculate the time required to get the same gradient duration with the target column:
Gradient step volume = Gradient duration x Target column volume
Gradient step time = Gradient step volume / Flow rate2
Using the above calculations, a gradient was determined for each specific column dimension as
demonstrated below in Table 2.13 and Table 2.14. In this example, a gradient for a 100 mm length x
2.1 mm diameter column with 1.9 µm particle size (Table 2.13) was converted to the equivalent
gradient for a 50 mm length x 2.1 mm diameter column with 1.9 µm particle size (Table 2.14).
Table 2.13 Gradient for a 100 mm length x 2.1 mm diameter column, 1.9 µm particle size
Length
(cm)
Diameter
(cm)
Particle
size (µm) Column
volume
(mL)
Flow rate
(mL/min)
Dwell volume system
(mL)
Column 10 0.21 1.9 0.35 0.4 0.4
Gradient Step Time
(mins) % A % B
Gradient volume
(mL)
Gradient duration
(min)
Step 1 0 95 5 N/A N/A
Step 2 5 95 5 2 5.78
Step 3 55 50 50 22 63.55
Step 4 59 50 50 23.6 68.17
Step 5 60 95 5 24 69.33
Step 6 65 95 5 26 75.1
66
Table 2.14 Gradient for a 50 mm length x 2.1 mm diameter column, 1.9 µm particle size
Length
(cm)
Diameter
(cm)
Particle
size (µm)
Column
volume
(mL)
Flow rate
(mL/min)
Dwell volume
system (mL)
Column 5 0.21 1.9 0.17 0.4 0.4
Gradient Target Time
(mins) % A % B
Target gradient
volume (mL)
Gradient duration
(mins)
Step 1 0 95 5 n/a n/a
Step 2 2.5 95 5 1 5.78
Step 3 27.5 55 45 11 63.55
Step 4 29.5 55 45 11.8 68.17
Step 5 30 95 5 12 69.33
Step 6 32.5 95 5 13 75.1
Using the optimum sample diluent, detection wavelength of 220 nm and an equivalent
gradient profile, a sample containing a mixture of Peptide 1 and ‗Sample set A‘ was analysed using a
series of columns with multiple different mobile phases as outlined previously in Table 2.2 and Table
2.4 (page numbers 47 and 48). For columns 2, 10, 12 and 14, each reagent was individually analysed
on each mobile phase system to determine the order of elution of the analytes for each system. The
mobile phase components chosen for the evaluation include commonly used reagents such as TFA,
formic acid, ammonium acetate, ammonium formate and sodium phosphate. For reproducibility, the
pH of any given mobile phase should be +/- 1.0 pH unit above or below the pKa of the solutes being
separated otherwise it could lead to asymmetric peaks that are broad, tail, split or shoulder [106].
Some of the analytes under investigation have low pKa values, such as HOAt at 3.28, 6-ChloroHOBt
at 3.35 and HOBt and Oxyma Pure at 4.60 [108]. However, some of the pKa/pKb values of the
analytes were unknown and some were quite high, such as TMU at pKb 12.00 and therefore more than
one mobile phase pH needed to be investigated to determine the optimum pH for the analysis [23].
The ionised form of the analytes are more polar and therefore exhibit less retention in RP-HPLC. As a
result, the pH needs to be lower than the pKa of the acidic analytes (ideally < 2 pH units) in order to
suppress the ionisation to achieve a good peak shape and good retention. Acetonitrile and methanol
were chosen as the organic solvents for the evaluation. Acetonitrile is the most commonly used
solvent in RP-HPLC because it is volatile (compatible with mass spectrometric detection), has low
viscosity and is practically transparent for UV detection for low wavelengths < 200 nm [107]. Each
column/mobile phase system was evaluated in terms of number of peaks resolved, the number of
peaks with a resolution with their nearest neighbour > 2, the number of peaks with retention factor
(k*) > 2, the number of peaks with tailing factors < 2, and the number of peaks with plate count >
2,000, as shown in Table 2.15, using the Aquity HSS C18 column as an indicative example.
It should be noted however that strictly speaking, efficiency is not defined in chromatographic
gradients. In order for efficiency to be calculated, there is an assumption that the mobile phase
composition is the same at the start of a peak, the peak apex, and the tail of a peak. In mobile phase
67
gradients, this is not the case. In fact, the solute molecules at the head of the peak ―experience‖ a
slightly lower solvent concentration relative to molecules in the bulk of the peak, and so slow down
slightly. Conversely, solute molecules at the tail of the peak experience slightly higher solvent
concentration and so move faster than molecules in the centre of the band. This phenomenon is partly
responsible for chromatographic zone focussing during mobile phase gradients. The authors fully
acknowledge therefore that, strictly speaking, the use of plate count determinations is not accurate
from a theoretical standpoint. However, for the remainder of this chapter (and indeed Chapter 3) we
have elected to use plate count as a means of evaluating peak width, merely for the sake of simplicity
in method development, rather than the more accurate measurement of average peak width across the
chromatogram, or a measure of other parameters such as peak capacity.
When retention factor k* is mentioned in this thesis, the reader should not the difference
between k (used for isocratic separations) and k* (used for gradient separations). In isocratic
separations the retention factor (k*) is a constant value during the separation and depends upon the
partition coefficient for the analyte in question. Conversely, in gradient methods, the retention factor
(denoted k*) is not constant, but rather, varies throughout the run. The symbol (k*) can be thought of
as the average k-value throughout the separation, and is equivalent to the isocratic k-value at the point
a band has moved halfway down the column. The k* value is calculated using the following formula:
m
g
VS
Ftk
15.1*
Where tg is the gradient time (minutes) F is the flow rate, S is a constant determined by the analyte
mass (usually 4 for analytes < 500 Da), ΔΦ is the change in volume fraction of organic (final %B
minus initial % B) and Vm is the column void volume (πr2L x 0.68).
The score evaluation (number of peaks resolved, the number of peaks with a resolution with
their nearest neighbour > 2, the number of peaks with retention factor (k*) > 2, the number of peaks
with tailing factors < 2, and the number of peaks with plate count > 2,000) was performed on each
column for each mobile phase system and the results are summarised in Table 2.16. The example in
Table 2.15 is shown as the first line of data in Table 2.16.
68
Table 2.15 Score evaluation of Acquity HSS C18 for each mobile phase system
Note: This column was arbitrarily chosen for illustrative purposes in order to demonstrate how scores were calculated. The data from the right column is
transposed in the first row of Table 2.16.
Mobile
phase
system
Mobile phase A
composition
Mobile phase B
composition
Total
peaks
resolved
No of
peaks
Rs
>2.0 k* range
No of
peaks
k* > 2
Plate count
range
No of
peaks
plate
count
>2,000
Tailing
range
No of
peaks
peak
tailing ≤
2.0 Score
1 0.1 % TFA 0.08 % TFA/ACN 10 8 1.45 - 24.93 9 5,500 - 30,500 10 1.01 - 2.32 9 46
2 0.1 % TFA 0.08 % TFA/MeOH 9 7 3.98 - 40.25 9 3,414 - 281,472 9 1.04 - 2.08 8 42
3 0.1 % Formic acid
0.08 % Formic acid
/ACN 9 6 2.00 - 23.49 9 5,303 - 51,921 9 1.08 - 5.51 7 40
4 0.1 % Formic acid
0.08 % Formic
acid/MeOH 8 4 3.93 - 36.82 8 502 - 25,128 7 1.08 - 2.96 6 33
5 10 mM CH3COONH4 pH 4.0 ACN 8 7 2.41 - 50.36 8 1,072 - 145,841 7 0.92 - 3.73 5 35
6 10 mM CH3COONH4 pH 4.0 MeOH 7 5 3.93 - 80.06 7 177 - 106,221 5 0.91 - 3.92 5 29
7 10 mM NH4HCO2 pH 3.0 ACN 8 6 4.28 - 48.90 8 1,379 - 11,124 7 1.09 - 1.60 8 37
8 10 mM NH4HCO2 pH 3.0 MeOH 9 6 8.13 - 78.00 9 2,643 - 117,748 9 1.07 - 2.51 6 39
9 10 mM NaH2PO4 pH 2.0 ACN 8 5 1.83 - 23.76 7 1,980 - 14,219 7 1.04 - 1.26 8 35
10 10 mM NaH2PO4 pH 2.0 MeOH 8 6 3.87 - 39.14 8 1,043 - 13,953 7 1.01 - 2.34 7 36
11 10 mM NaH2PO4 pH 7.0 ACN 4 1 -0.23- 11.62 3 125 - 4,048 1 0.85 - 2.60 2 11
12 10 mM NaH2PO4 pH 7.0 MeOH 6 4 1.00 - 51.85 4 308 - 3,963 3 1.18 - 1.89 6 23 *Analytes evaluated include ‗Sample set A‘ and Peptide 1
69
Table 2.16 Summary of score evaluation for all columns for each mobile phase system
Colu
mn
s Mobile phase system
Evaluation of column and
mobile phase system
Column 1 2 3 4 5 6 7 8 9 10 11 12
No. of mobile
phase systems
≥ 40
Total
overall
score
Acquity HSS C18 46 42 40 33 35 29 37 39 35 36 11 23 3 406
Acquity HSS C18 SB 29 37 31 29 30 28 26 23 35 38 19 25 0 349
Acquity HSS T3 47 43 39 37 42 38 39 40 43 40 29 26 6 463
Acquity BEH300 C4 35 33 33 31 22 21 24 23 38 33 12 12 0 315
Acquity BEH C18 36 43 31 37 32 36 30 38 29 39 21 26 1 398
Acquity BEH RPC18 Shield 33 29 27 32 26 27 26 26 23 28 18 22 0 317
Acquity BEH Phenyl 30 35 39 30 37 36 38 36 37 44 29 27 1 418
Agilent Eclipse Plus C18 43 48 41 42 35 36 36 36 40 43 29 30 6 459
Agilent Eclipse Plus C8 41 49 37 42 25 36 32 40 33 40 33 36 5 444
Agilent Zorbax SB C18 40 43 31 31 29 29 33 29 28 34 30 33 2 390
Phenomenex Kinetix 31 31 26 32 31 37 32 33 42 44 26 21 2 386
Halo C18 33 41 30 37 29 33 31 33 36 33 19 22 1 377
YMC Ultra HT Hydrosphere
C18 39 38 35 37 39 41 35 37 44 39 31 32 2
447
YMC Ultra HT Pro C18 41 42 39 40 37 42 35 38 41 46 23 27 6 451
YMC Triart C18 42 40 33 39 43 42 40 37 43 43 35 37 7 474
Acclaim RSLC 120 C18 39 38 40 39 34 35 29 30 34 39 36 31 1 424
Thermo Hypersil Gold 39 41 42 43 33 34 40 39 30 30 26 30 4 427
Mobile phase system total
overall score 644 673 594 611 559 580 563 577 611 649 427 460 *Analytes evaluated include ‗Sample set A‘ and Peptide 1
*The composition of the mobile phase systems can be cross referenced with Table 2.15.
*The odd numbered mobile phase systems use acetonitrile as the organic modifier and the even numbered mobile phase systems use methanol as the organic modifier.
70
Table 2.16 details the overall score for each column/mobile phase system. Different columns
can vary in plate number, band symmetry, retention, band spacing, and lifetime [61]. The maximum
possible score was determined as 60, if all 12 peaks within the mix were separated with resolution >
2, peak tailing ≤ 2 and r > 2. Since the conditions being evaluated were not optimised for parameters
such as temperature, pH, concentration, etc., at this stage in the developmental work, all
column/mobile phase systems with a score of > 40 were deemed acceptable for further evaluation. A
score of 40 meant that at least 8 of the peaks evaluated were resolved, most of which met the criteria
for resolution > 2, retention factor (k*) > 2, tailing factors < 2, and plate count > 2,000.
The total overall score (last column on Table 2.16) was calculated by adding all of the
individual scores for a given column. The mobile phase system total overall score (last row of Table
2.16) was calculated by adding all individual scores for a given mobile phase system.
On all columns, HOAt, HBTU and TBTU eluted very early and therefore they are the most
hydrophilic analytes. Oxyma Pure, 6-ChloroHOBt, PyClocK and the Peptide 1 were the most retained
analytes and therefore the most hydrophobic. None of the 204 experiments demonstrated the ability to
resolve HBTU and TBTU or 6-ChloroHOBt and PyClocK. HBTU and TBTU can‘t be resolved
because the analytes only differ by their counter ion (as shown in Table 2.7, page 57) and therefore
are the same compound when dissolved [109].
The Acquity BEH 300 C4 was the worst performing column in the investigation, achieving
the lowest overall score of 315. The column resulted in poor retention of the analytes and as a result,
the column demonstrated poor performance with no mobile phases demonstrating a score above 40.
This was expected as sample retention typically increases for bonded phases of greater length (C18 >
C8 > C3 > C1) [94]. Also, this column was of pore size 300 Å, which is typically used for high
molecular weight analytes [106]. Smaller pore size columns were determined to be better for the
separation of these low molecular weight analytes. Figure 2.3 shows a sample chromatogram on the
Aquity BEH 300 C4 column, clearing showing poor retention relative to an Acquity BEH C18, which
was chosen for comparative purposes. Mobile phase system 1 was arbitrarily selected so that a useful
comparison can be made.
Acquity HSS C18 SB (total score of 349) and Acquity BEH Shield RP C18 (total score of
317) were also determined as poor performing columns, with no mobile phase systems resulting in a
score above 40 for either column. Acquity HSS C18 SB is a non-end capped column and all
chromatograms displayed poor peak shape. End-capping is a process which is used to react silica gel
silanol groups that may remain after reaction, with a large silylating agent such as
octadecyltrichlorosilane [106]. The column is said to be end capped when a small silylating reagent
(such as trimethylchlorosilane or dichlorodimethylsilane) is used to react with residual silanol groups
on a silica gel-based packing surface [106]. It is used to minimize undesirable adsorption of basic,
ionisable, and ionic compounds and therefore, the poor peak shape obtained during the analysis of
HSS C18 SB is potentially due to the lack of end-capping [106]. Figure 2.4 shows a sample
71
chromatogram on the Acquity HSS C18 SB column, clearly showing poor peak shape when compared
with an Acquity HSS C18 column, which is end capped. Again, mobile phase system 1 was arbitrarily
selected for comparative purposes. For this separation, it was concluded that end-capped columns
were demonstrated to be better than non-end-capped columns, as would be expected.
Figure 2.3: Comparison of retention on (a) Acquity BEH C18 and (b) Acquity BEH 300 C4.
(Chromatographic conditions:, Mobile phase A: 0.1 % TFA, Mobile phase B: 0.08 % TFA in
acetonitrile, Gradient program: A5 for (a) and A4 in (b) in Appendix 1, Injection volume: 5 µL,
Column temperature: 25 oC, Detection wavelength: 220 nm.
72
Figure 2.4: Comparison of retention on (a) Acquity HSS C18 (end capped) column and (b) Acquity
HSS C18 SB (non-end capped). (Chromatographic conditions:, Mobile phase A: 0.1 % TFA, Mobile
phase B: 0.08 % TFA in acetonitrile, Gradient program: A3 in Appendix 1, Injection volume: 5 µL,
Column temperature: 25 oC, Detection wavelength: 220 nm.
A comparison of the use of acetonitrile or methanol as the eluting solvent in the mobile phase
system was performed. In Table 2.16, the odd numbered mobile phase systems use acetonitrile as the
organic modifier, whereas the even mobile system numbering use methanol. Acetonitrile as an eluting
solvent resulted in an overall score of 3398 (addition of score of all 102 experiments performed with
acetonitrile as the eluting solvent), whereas methanol resulted in an overall score of 3550. This could
be due to methanol being the weaker eluting solvent and therefore resulting in better retention of early
eluting peaks and a better resolution of closely eluting peaks. Methanol demonstrated better
73
selectivity for the polar compounds; however sharper peaks were obtained using acetonitrile as
observed in Figure 2.5.The order of elution of the reagents is the same for both acetonitrile and
methanol, however acetonitrile resulted in the separation of TMU and COMU and also HCTU and
Oxyma Pure, whereas they co-eluted with the use of methanol. Acetonitrile was chosen as the
optimum eluting solvent for further optimisation studies, due to improved peak shape. Sharp
symmetrical peaks are necessary to achieve low detection limits, low relative standard deviation
(RSD) between injections and reproducible retention times. For this separation, acetonitrile was
demonstrated to be better than methanol for the separation of the analytes.
Figure 2.5: Comparison of peak shape on Acquity HSS C18 using (a) acetonitrile and (b) methanol as
organic modifier in mobile phase B. Chromatographic conditions: Mobile phase A: 0.1 % TFA,
mobile phase B: 0.08 % TFA in acetonitrile or methanol. Gradient program: A3 in Appendix 1,
Injection volume: 5 µL, Column temperature: 25 oC, Detection wavelength: 220 nm.
74
The best column was determined as YMC Triart C18, with the greatest overall score of 474
and 7 mobile phase systems with a score > 40. A holistic evaluation of all mobile phases containing
acetonitrile by comparing the scores (on the bottom row of Table 2.16) revealed that TFA was the
best mobile phase (score of 644), followed by sodium phosphate pH 2 (score of 611), formic acid
(score of 594), ammonium formate (score of 563), ammonium acetate (score of 559) and then the
worst mobile phase system was obtained for sodium phosphate pH 7 (score of 427). A comparison of
sodium phosphate pH 2 and sodium phosphate pH 7 as shown in Figure 2.6, demonstrates the poor
retention of some of the analytes at higher pH. This is due to the ionisation of acids (most of reagents
in ‗Sample set A‘) and bases as the pH increase, which results in a decrease of retention of acids and
increase in retention of bases [61].
Figure 2.6: Comparison of retention on Acquity HSS C18 using (a) sodium phosphate pH 2 and (b)
sodium phosphate pH 7 as mobile phase A. Chromatographic conditions: Mobile phase B:
Acetonitrile, Gradient program: A3 in Appendix 1, Injection volume: 5 µL, Column temperature: 25
oC, Detection wavelength: 220nm.
75
All column/mobile phase systems with a score of > 40 were deemed acceptable for further
evaluation and therefore this reduced the number of column/mobile phase systems from 204 to 46.
There was very little difference between the column/mobile phase systems with scores over 40 and
the results did not demonstrate that any particular column/mobile phase system that was superior
above all others. Therefore other performance evaluation criteria (i.e. mass spectrometry
compatibility) were necessary to distinguish optimum column/mobile phase system over and above
the ‗scoring system‘ previously described. The ideal method would be directly transferrable to a mass
spectrometer and therefore, the 46 columns/mobile phase systems were further evaluated depending
on the mass spectrometry (MS) compatibility of the mobile phase system. TFA and sodium phosphate
are not mobile phase components that are used in mass spectrometry and therefore this reduced the
number of experiments from 46 to 17, as outlined in Table 2.17. TFA is a volatile mobile phase
component however, it can suppress ionization in the LC-MS interface, causing a drop in signal and
therefore it is not an ideal for LC-MS [110].The ideal method would be compatible with the mass
spectrometer because this would allow the confirmation of the molecular weight of all the
compounds. Sodium phosphate is not volatile and can also result in the unwanted formation of sodium
adducts.
Table 2.17 Summary of mass spectrometry compatible column and mobile phase systems
Column Mobile phase system Score
Acquity HSS C18 3 40
Acquity HSS T3 5 42
8 40
Agilent Eclipse Plus C18 3 41
4 42
Agilent Eclipse Plus C8 4 42
8 40
YMC Ultra HT Hydrosphere C18 6 41
YMC Ultra HT Pro C18 4 40
6 42
YMC Triart C18
5 43
6 42
7 40
Acclaim RSLC 120 C18 3 40
Thermo Hypersil Gold
3 42
4 43
7 41 Note: Mobile phase 1, 2, 9, 10, 11 and 12 are not eligible for further study since they contain TFA and sodium phosphate respectively. They are therefore excluded from this table.
When acidic and basic samples are present in the sample, it is strongly advisable to control
mobile phase pH by adding a buffer [61]. Mobile phase pH can be one of the most important variables
in the control of retention in a reversed-phase HPLC separation and therefore is a very powerful tool
76
for method development [110]. This would therefore eliminate formic acid as a mobile phase,
reducing the number of experiments to 9, as seen in Table 2.18.
Since YMC Triart C18 was determined as the best performing column and it was also the
column with the most mobile phase systems in the final selection (see Table 2.18 below), this was
determined as the best column for further evaluation. This column gave optimum results using both
ammonium acetate (mobile phases 5 and 6) and ammonium formate (mobile phases 7 and 8). Both
mobile phase systems result in a decreasing baseline with an increasing of amount of acetonitrile. The
pKa of ammonium acetate is 4.8 and 9.2 and the pKa of ammonium formate is 3.8 and 9.2. The buffer
should be used to control pH over a range of pKa +/- 1.0 and therefore ammonium acetate can be used
at pH 3.8 to 5.8 and 8.2 to 10.2 [61]. Ammonium formate can be used at pH 2.8 to 4.8 and also 8.2 to
10.2. This means that although the pH of the mobile phases can be adjusted outside of the range,
however there is negligible buffering capacity beyond +/- 1.0 pH unit about the pKa [110]. Based on
the analysis above where the analysis of the analytes at a high pH using sodium phosphate resulted in
poor resolution of peaks, ammonium formate and acetonitrile were chosen as the mobile phase to
further evaluate for the separation of the analytes, as this mobile phase can be used at a lower pH
range, which could be optimum for the separation of the analytes.
Table 2.18 Summary of optimum mobile phase systems (based upon selected scoring system)
Column Mobile phase system Score
Acquity HSS T3 5 42
8 40
Agilent Eclipse Plus C8 8 40
YMC Ultra HT Hydrosphere C18 6 41
YMC Ultra HT Pro C18 6 42
YMC Triart C18
5 43
6 42
7 40
Thermo Hypersil Gold 7 41
Note: Mobile phase with formic acid alone are excluded from this table
2.3.2 Design of experiments (DoE)
After the optimum stationary phase and mobile phase were selected, further optimisation was
performed. Modde 9 software was used to compile an experimental design space where all of the
selected parameters are varied at the same time. A DoE is a process used to maximise the information
obtained regarding the impact of the parameters on the chromatographic separation with the minimum
number of experiments. The factors under investigation included the concentration of the mobile
77
phase, pH of the mobile phase, column temperature, flow rate and gradient change. A buffer
concentration of up to 50 mM is adequate for small molecules and therefore the concentration range
investigated was 5 mM to 50 mM [111]. The pKa of ammonium formate is 3.8 and 9.2, therefore these
were chosen as the pH values for the investigation [61]. The YMC Triart column has a maximum
temperature limit of 50 ºC for high pH mobile phases and therefore the column temperature range
chosen for the investigation was 20 ºC to 50 ºC [97]. Column temperature can have a significant
impact on the separation of peptides, with reduced retention typically observed for increased
temperature alongside changes in selectivity [107]. A flow rate of range of 0.3 mL/min to 0.5 mL/min
and a 0.2 % to 1.2 % change in mobile phase B per minute were chosen as the other parameter ranges
to be investigated.
The DoE was a full factorial DoE of Resolution V+ design, which is capable of resolving all
the main effects and the two factor interactions. In other words, the software can isolate and quantify
the effects of each main factor and each two-factor interaction [112]. This DOE study involved 19
experiments (16 + 3 centre points). The centre point experiments were used to ensure there were no
external influences such as a system bias, environmental changes, and random skewing. The values of
the factors for the centre point experiments were calculated from the average of each particular factor,
for example: column temperature was selected as 35 ºC, the average of the addition of 20 ºC and 50
ºC. The responses evaluated were the overall number of peaks resolved, the % of peaks resolved that
demonstrate resolution > 2, the % of peaks with k* > 2 and the % of peaks with plate count > 2,000.
A resolution of 2 or greater is generally desirable for rugged methods and therefore a minimum
resolution of 2 was the criteria set for the development experiments [61]. The number of theoretical
plates is a measure of column efficiency and this depends on the elution time and peak width but the
number should typically be > 2,000 and therefore a criterion for number of theoretical plates was set
at > 2,000 for all method development experiments [61]. The results of each DoE experiment are
outlined in Table 2.19.
78
Table 2.19 DoE evaluation and corresponding chromatographic performance criteria.
Experiment parameters Results
Exp
Name pH
Conc
(mg/mL)
Flow rate
(mL/min)
Temp
(°C)
% B
Change/min
Peaks
resolved
R >2
(%)
k*>2
(%)
Plate
count >
2,000
N1 3.8 5 0.3 20 1.2 8 62.5 100 87.5
N2 9.2 5 0.3 20 0.2 7 14.29 85.71 14.29
N3 3.8 50 0.3 20 0.2 9 66.67 100 100
N4 9.2 50 0.3 20 1.2 6 66.67 100 66.67
N5 3.8 5 0.5 20 0.2 8 75 100 87.5
N6 9.2 5 0.5 20 1.2 7 14.29 71.42 14.29
N7 3.8 50 0.5 20 1.2 9 55.56 100 77.78
N8 9.2 50 0.5 20 0.2 7 42.86 85.71 57.14
N9 3.8 5 0.3 50 0.2 8 87.5 100 75
N10 9.2 5 0.3 50 1.2 6 33.33 66.67 16.67
N11 3.8 50 0.3 50 1.2 8 75 100 75
N12 9.2 50 0.3 50 0.2 6 33.33 83.33 50
N13 3.8 5 0.5 50 1.2 8 62.5 100 87.5
N14 9.2 5 0.5 50 0.2 6 50 66.67 33.33
N15 3.8 50 0.5 50 0.2 8 62.5 100 87.5
N16 9.2 50 0.5 50 1.2 6 50 66.67 50
N17 3.8 27.5 0.4 35 0.7 9 55.56 100 77.78
N18 3.8 27.5 0.4 35 0.7 9 55.56 100 77.78
N19 3.8 27.5 0.4 35 0.7 9 55.56 100 77.78
A replicate plot was constructed to show the variation among the three centre point
experiments (experiments N17, N18 and N19) and to demonstrate the reproducibility of the model.
The variation in the replicate plots for retention factor (k*), resolution between critical peak pair, peak
plate count and number of peaks resolved demonstrated minimal variation in the entire investigation
series. It was therefore concluded that the replicate error would not complicate the data analysis.
A regression model was constructed to evaluate the summary of fit plot to determine if the
results for each factor were valid. A ‗valid‘ model has properties (R2 goodness of fit, Q
2 goodness of
prediction, reproducibility) close to 1.0. In this case, the regression plot for number of peaks resolved
indicated that the model was acceptable (R2 > 0.8, Q
2 > 0.5 and the difference R
2- Q
20.2-0.3), with
R2 of 0.89 and Q
2 of 0.78.
79
Figure 2.7: Regression model for number of peaks resolved
The regression model for the % of peaks with k* > 2 and % of peaks with plate count > 2,000 were
also valid with results of R2 of 0.83 and Q
2 of 0.57, and R
2 of 0.83 and Q
2 of 0.60, respectively.
However, the regression model for the % of peaks with resolution > 2 was determined to be invalid
with R2 of 0.56 and Q
2 of 0.04 and therefore this data could not be used to accurately evaluate the
impact of the 5 factors on resolution.
A coefficient plot was then compiled to determine the influences, if any, of the 5 factors on
the number of peaks resolved, % of peaks with k* > 2 and % of peaks with plate count > 2,000.
Figure 2.8 shows the coefficient plot for the response for the number of peaks resolved, indicating that
pH had the largest effect on the number of peaks resolved. It had a large negative effect on the
number of peaks resolved (i.e. increasing pH led to a reduction in the number of peaks resolved).
Column temperature was the next most influential factor with a negative effect. Buffer concentration
and flow rate had a smaller positive effect on the number of peaks resolved and a small negative
effect was observed for % change in mobile phase B per minute.
Figure 2.8: Coefficient plot for number of peaks resolved
80
Figure 2.9 shows the coefficient plot for the response for the % of peaks with k*>2, indicating that pH
also had a largest negative effect on the % of peaks with k*>2. Column temperature was also the next
most influential factor with a negative effect. Flow rate and % change in mobile phase B per minute
had a smaller positive effect on the % of peaks with k*>2 and a small positive effect was observed for
buffer concentration. The error bars details the ± 95 % confidence intervals for the results of each
factor.
Figure 2.9: Coefficient plot for the % of peaks with k*>2
Figure 2.10 shows the coefficient plot for the response for the % of peaks with plate count >2,000,
indicating that pH also had a large negative effect on the % of peaks with plate count >2,000. Buffer
concentration was the next most influential factor with a positive effect. Column temperature and %
change in mobile phase B per minute had a smaller negative effect on the % of peaks with plate count
>2,000 and buffer concentration demonstrating a small positive effect.
Figure 2.10: Coefficient plot for the % of peaks with plate count > 2,000
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A contour plot was compiled to indicate/predict the conditions for optimum chromatographic
results. The contour plot is a graphical tool, which utilizes the regression coefficients to make
predictions of where to position new experiments. Contour plots were used to indicate/predict where
the ‗optimum‘ chromatographic results can be attained with respect to each factor. The 3 less
influential factors (flow rate, column temperature and change in % B per minute) were held constant
and the effect of pH and buffer concentration on all 4 responses are observed in Figure 2.11.
Figure 2.11: Contour plot for all chromatographic performance criteria with varying pH and buffer
concentration. (The flow rate was 0.4 mL/min, column temperature was 35ºC, the % B change/min
was set at 0.7 % change/minute).
The red region is the optimum region in the contour plot demonstrating the highest overall
score (i.e. chromatographic conditions which resulted in the greatest number of peaks resolved,
greatest number of peaks with a resolution with their nearest neighbour > 2, greatest number of peaks
with retention factor (k*) > 2 and the greatest number of peaks with tailing factors < 2). Conversely,
the blue region represents the opposite scenario, i.e. poorest chromatographic performance. Based on
the three coefficients plots and the contour plots, pH is the most influential on the responses, with a
low range pH giving the optimum results. Buffer concentration had a small effect on the responses,
with a larger buffer concentration potentially giving the optimum results. The flow rate, column
temperature and percentage change in mobile phase B per minute all have minimal influence on the
response, however a slower flow rate, low column temperature and a smaller percentage change in
mobile phase B per minute potentially gives the optimum results.
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2.3.3 Evaluation of optimum pH range and column temperature
Based on the DoE in Section 2.3.2, a low pH range was recommended for the best
chromatographic results. The pKa of ammonium formate is 3.8 and as a result, the pH range that was
evaluated was 2.8 to 4.8, within the allowed criteria of +/- 1.0 pH units of the pKa value [61].
Figure 2.12: Effect of buffer pH upon retention. Buffer pH was (a) pH 2.8, (b) 3.8 and (c) 4.8, all at a
column temperature of 35 °C (Mobile phase: 10 mM ammonium formate and acetonitrile, column:
YMC Triart C18, flow rate: 0.3 mL/min, injection volume: 5 µL, detection wavelength: 220 nm and
gradient profile: A15 in Appendix 1).
The DoE outlined that the effect of column temperature was minimal, with lower column
temperature potentially giving the optimum results. In order to evaluate the pH range of 2.8 to 4.8 and
to further evaluate temperature under these conditions, a mix containing ‗Sample set A‘ was evaluated
in terms of resolution, plate count, tailing, retention factor (k*) and absorbance response at pH 2.8,
3.8, and 4.8, each at temperatures of 25 °C, 35 °C and 45 °C. Figure 2.12 demonstrates the effect of
change of pH from 2.8 to 4.8 on the separation of the analytes at 35 °C. The retention of early eluting
peaks increased as pH decreased, however the higher pH resulted in better resolution of early eluting
83
peaks. The small changes in pH had a significant impact on the separation due to the analytes being
ionisable. The increase in retention at lower pH values was expected because decreasing the pH
results in the analytes becoming more non-polar which therefore resulting in better retention. The
experiment at pH 2.8 gives a poor absorbance response and noisy baseline relative to higher pH. This
is possibly due to the large amount of formic acid added to the mobile phase to achieve the low pH.
The experiment at pH 3.8 resulted in the co-elution of early eluting peaks and therefore pH 4.8 was
chosen as the optimum pH.
Figure 2.13 demonstrates the effect of temperature 25 °C, 35 °C and 45 °C at a pH of 4.8. The
retention of early eluting peaks increased as temperature decreased and the lower temperature was
also optimum for the separation of the critical peak pair of TMU and COMU.
Figure 2.13: Effect of column temperature upon retention at pH 4.8. Column temperature was (a) 25
°C, (b) 35 °C and (c) 45 °C. (Mobile phase: 10 mM ammonium formate and acetonitrile, column:
YMC Triart C18, flow rate: 0.3 mL/min, injection volume: 5 µL, detection wavelength: 220 nm and
gradient profile: A15 in Appendix 1).
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2.3.4 Evaluation of column temperature using 10 mM ammonium formate pH 4.8
Using the optimised pH of 4.8 and buffer concentration of 10 mM, the entire column
temperature range was evaluated from 10 °C to 50 °C (in 5 °C intervals) to ensure 25 °C was the
optimum temperature, as determined in Section 2.3.3. Figure 2.14 demonstrates the effect of
temperature change and as determined in Section 2.3.3, the retention of the first peak is greater at
lower temperatures. The main impact of temperature on the separation is the effect on the critical peak
pair. The critical peak pair changes from HCTU and TMU at low column temperature, to COMU and
Oxyma Pure at 30 °C, and then to TMU and COMU above 40 °C column temperature. Based on this,
the optimum column temperature was confirmed to be 25 °C.
Figure 2.14: Comparison of column temperature of (a) 15 °C, (b) 25 °C and (c) 40 °C. (Mobile
phase: 10 mM ammonium formate and acetonitrile, column: YMC Triart C18, flow rate: 0.3 mL/min,
injection volume: 5 µL, detection wavelength: 220 nm and gradient profile: A15 in Appendix 1).
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2.3.5 Analysis of additional coupling reagents
During the method development, additional coupling reagents were introduced into the scope
of the method development due to investigational work on early development compounds within
Ipsen Manufacturing Ireland LTD. Sample information was therefore required on the additional
reagents, as per Section 2.3.1. The chemical structure of each additional reagents of ‗Sample set B‘ is
outlined in Table 2.20.
Table 2.20 Chemical structure of additional peptide coupling reagents and by-products added to the
study.
Compound Structure Details
PyBrOP
[101, 83]
Molecular weight: 466.2g mol-1
PyBOP
[48,77]]
Molecular weight: 520.39g mol-1
TCTU
[31,90]
Molecular weight: 355.53g mol-1
DIC
[101,91]
Molecular weight: 126.2 mol-1
DIU
[78,113]
Molecular weight: 144.2 mol-1
The solubility and order of solvent addition to dissolve each of these reagents was assessed as
per Section 2.2.3 and the results are outlined in Table 2.21 and Table 2.22. DIC is a solution and was
fully miscible in all solutions at each concentration, as determined by a visual inspection.
86
Table 2.21 Solubility of additional reagents added to the study
Compound Solvent Description
Approx solubility
concentration
TCTU 0.1 M AcOH Slightly soluble 1 mg/mL
H2O Slightly soluble 1 mg/mL
MeOH Slightly soluble 1 mg/mL
ACN Soluble 33.33 mg/mL
PyBOP 0.1 M AcOH Very slightly soluble 0.1 mg/mL
H2O Very slightly soluble 0.1 mg/Ml
MeOH Slightly soluble 1 mg/mL
ACN Freely soluble 100 mg/mL
PyBrOP 0.1 M AcOH Very slightly soluble 0.1 mg/mL
H2O Very slightly soluble 0.1 mg/mL
MeOH Slightly soluble 1 mg/mL
ACN Freely soluble 100 mg/mL
DIU 0.1 M AcOH Slightly soluble 1 mg/Ml
H2O Slightly soluble 1 mg/mL
MeOH Soluble 33.33 mg/mL
ACN Sparingly soluble 10 mg/mL
Table 2.22 Order of diluent addition for dissolving additional reagents.
Product
Initial
diluent Second diluent
Third
diluent
TCTU ACN MeOH H2O
PyBOP ACN MeOH H2O
PyBrOP ACN MeOH H2O
DIU MeOH ACN H2O
2.3.5.1 Determination of optimum detection wavelength for additional reagents
Each additional reagent was evaluated between 210 nm and 400 nm on a photodiode array to
ensure they could be detected at the selected wavelength of 220 nm. Figure 2.15 demonstrates that
DIU and PyBOP have minimal absorbance at 220 nm and therefore the wavelength for analysis was
changed to 215 nm.
87
Figure 2.15: PDA profile of additional analytes. The red dotted line represents the optimum
wavelength.
2.3.6 Optimisation of buffer pH for separation of ‘Sample set B’
The addition of extra reagents to the study necessitated the re-optimisation of buffer pH. A
mix containing ‗Sample set B‘ was evaluated in terms of resolution, plate count, tailing, retention
factor (k*) and sensitivity at pH 2.8, 2.9, 3.0, 3.1, 3.2, 3.3, 3.8, 4.3 and 4.8. The pH affects the
selectivity and the critical peak pair change and a pH of 3.3 was chosen as the optimum based on the
results outlined in Figure 2.16. Table 1 in Appendix 3 details that that lowest resolution
(resolution=1.3) was achieved using pH 3.3 (with the exception of pH 3.8, for which resolution could
not be calculated), however as observed in Figure 2.16, an increase in the pH resulted in a change of
critical peak pair and a significant reduction in k of the first peak. A lower pH than 3.3 resulted in an
increase in peak tailing and therefore pH 3.3 was chosen as the best option to meet the
chromatographic criteria for both critical peak pairs of TBTU/HBTU and HoAt and HoBt and HCTU.
88
Figure 2.16: Effect of mobile phase pH upon retention for Sample set B. (Mobile phase: 10 mM
ammonium formate and acetonitrile, column: YMC Triart C18, flow rate: 0.3 mL/min, injection
volume: 5 µL, column temperature: 25ºC, detection wavelength: 215 nm and gradient profile: A15 in
Appendix 1).
2.3.7 Optimisation of flow rate for Sample set B
The flow rate of the mobile phase was evaluated for the separation of all reagents in ‗Sample
set B‘. A mix containing each reagent in ‗Sample set B‘ were evaluated in terms of resolution, plate
count, tailing, retention factor (k*) and absorbance response at flow rates of 0.25 mL/min, 0.30
mL/min and 0.35 mL/min. The higher flow rate resulted in better resolution of the critical peak pair;
however the lower flow rate resulted in a better retention of early eluting peaks as shown in Table 2
Appendix 3. As a result, a flow rate of 0.30 mL/min was selected to give the optimum results for both
resolution and plate count.
2.3.8 Re-evaluation of column temperature for Sample set B
The column temperature was re-evaluated following the addition of new peptide reagents to
determine the impact of temperature on results. Each reagent was evaluated in terms of resolution,
plate count and retention factor (k*) at column temperature 10 °C – 45 °C using a 10 mM ammonium
acetate buffer pH 3.3. Increasing temperature decreased the plate count and k* of the first peak as
detailed in Table 3 in Appendix 3. It had limited effect on tailing and resolution of the critical peak
89
pair was suspected to be better at a mid-range temperature and therefore 25 °C was chosen as the
optimum temperature.
2.3.9 Evaluation of final percentage acetonitrile required for the gradient
An investigation was performed to determine the effect of percentage acetonitrile on the last
eluting peak, PyBrOP. Three experiments were performed by varying the final percentage of the
acetonitrile within the same time frame. Table 4 in Appendix 3 details that the retention time (Rt) of
PyBrOP decreased with increased % acetonitrile. Significant tailing was observed for a final %
acetonitrile of 30 % (tailing = 2.0). This is possibly due to the elution strength of acetonitrile not being
strong enough to elute PyBrOP effectively such that it was slowly eluted from the column, resulting in
tailing. There is no difference in tailing between 40 % and 50 % acetonitrile and as a result, a
minimum of 40 % acetonitrile was selected as the final percentage acetonitrile to ensure timely elution
of PyBrOP.
2.3.10 Evaluation of optimum buffer concentration
The concentration of ammonium formate was evaluated following the selection of optimum
pH, flow rate and column temperature. Each reagent was evaluated in terms of resolution, plate count
and retention factor (k*) at ammonium formate concentration 5 mM to 40 mM. Table 5 in Appendix
3 demonstrates that an increase in buffer concentration resulted in an increase in the resolution of the
critical peak pair and also an increase in k* value of the first peak. Buffer concentration appears to
have minimal effect on plate count and tailing. However, increasing concentration had a significant
impact on AU response (from absorbance = 2.4 AU to absorbance = 0.2 AU), with higher
concentration resulting in poor AU response. As a result, a concentration range of < 15 mM was
required to ensure a high AU response was achieved. Since low concentration of ammonium formate
resulted in a poor resolution between the critical peak pair, a mid-range concentration of 15 mM was
chosen to obtain the optimum compromise between both criteria.
2.3.11 Final optimisation of buffer pH for Sample set B (to account for AU response)
The previous evaluation of pH of the mobile phase did not include the assessment of AU
response. As a result of the effect of concentration on AU response, the pH of the mobile phase was
re-evaluated to ensure the optimum pH has been chosen for all of the investigative parameters. It was
decided to widen the scope of the pH to include additional pH data points within the allowed range of
2.8 to 4.8 pH. Table 6 in Appendix 3 demonstrates that increasing pH results in the increase of
resolution of the critical peak. A mid-range pH from 3.6 to 3.9 gave the optimum plate count result,
with higher and lower pH of five a lower plate count result. A pH of 2.8 to 3.8 resulted in the same k
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value for the first peak, with k* value decreasing as pH increases from 3.8 to 4.8. A pH of 3.8 to 4.8
resulted in the same high AU response, with a decrease in AU response value as pH decreases from
3.8 to 2.8. A change in pH had minimal effect on tailing. The most important response was increasing
AU because other parameters can be altered by changing the gradient profile and as a result, the
optimum pH was determined as 4.2.
2.3.12 Evaluation of chromatographic gradients for separation of peptide synthesis
reagents and by-products
Until this point in the chapter (method development following the addition of further reagents
to the study), all chromatographic parameters were optimised with the exception of the gradient. As a
result, the final step of method development for the separation of Sample set B was gradient
optimisation as described below. Using a buffer of 15 mM ammonium formate pH 4.2 as mobile
phase A, gradients were varied in terms of hold times and percentage of mobile phase B, to determine
the optimum gradient for the resolution of the critical peak pair as well as other chromatographic
parameters (adequate retention of the first peak, tailing). The flow rate was also modified within
gradients to evaluate the impact of flow rate changes throughout the gradient profile. Table 7 in
Appendix 3 demonstrates that the gradient had very little impact on tailing and AU response. The
flow rate and acetonitrile concentration had a significant impact on the separation. The optimum
results were determined using gradient 12, as detailed in Table 2.30.
Table 2.23 Final optimised gradient program.
Time (min) Flow rate (mL/min) Mobile phase A Mobile phase B
Initial 0.275 97 % 3 %
9.00 0.275 97 % 3 %
9.01 0.3 97 % 3 %
12.00 0.3 92.5 % 7.5 %
12.01 0.4 87.5 % 12.5 %
16.00 0.4 60 % 40 %
22.00 0.4 97 % 3 %
23.00 0.4 97 % 3 %
26.00 0.275 97 % 3 %
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2.3.13 Final method for the detection of 14 peptide coupling reagents, additives and
associated by-products
Following investigation of multiple columns, several mobile phase systems and the
refinement of the method parameters such as mobile phase concentration, pH, column temperature
and gradient flow rate, a UHPLC method was established for the simultaneous determination of
peptide coupling reagents, additives and by-products used in peptide synthesis. Coupling reagents
HBTU and TBTU differ only by their counter-ion and are therefore detected as the same peak. This is
also the same case for HCTU and TCTU. PyBOP is not stable and as a result, it is detected as its more
stable by-product HOBt. DIC is also unstable and results in the formation of DIU, which it is detected
as. This is also the case for PyClocK, which degrades to its more stable by-product, 6-ChloroHOBt.
The critical peak pair of the final method is Oxyma Pure and 6-ChloroHOBt/PyClock, with a
resolution of 2.9. The final method is compatible with mass spectrometry and the chromatogram is
shown in Figure 2.17.
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Figure 2.17: Final optimised separation for the detection of 14 peptide coupling reagents, additives and associated by-products in the presence of 4 IMIL
peptides (Column: YMC Triart C18, Mobile phase A: 15 mM ammonium formate pH 4.2, Mobile phase B: acetonitrile, flow rate: 0.3 mL/min, injection
volume: 5 µL, column temperature 25ºC, detection wavelength: 215 nm and gradient profile: Table 2.32)
93
2.4 Conclusions
In conclusion, a fast, reliable ultra-high performance liquid chromatography method for the
simultaneous determination of peptide coupling reagents, additives and by-products used in peptide
synthesis, has been developed. Using a YMC Triart reverse-phase UHPLC column with particle size
of 1.9 µm, the UV assay can detect 14 commonly used peptide synthesis reagents in the presence of 4
peptides within a run time of 26 minutes. This rapid UHPLC method is directly transferable onto LC-
MS and offers significant advantages over current HPLC methods with long run times and methods
that can only detect single analytes.
94
__________________________________________________________________________
Chapter 3
The validation of a UHPLC method for the analysis of peptide coupling reagents, additives and
associated by-products during peptide synthesis
__________________________________________________________________________
95
3.1 Introduction
The determination of peptide coupling reagents, additives and associated by-products is
important during peptide synthesis to ensure the concentration of these products are below the
threshold of toxicological concern in the final peptide. The analytical method used to generate results
about the characteristics of drug related samples needs to be reliable and generate accurate results.
TMU, HOBt, HCTU, HBTU, 6-ChloroHOBt, TBTU, PyClocK, Oxyma Pure COMU, DIU, DIC,
PyBOP, and TCTU are peptide coupling reagents, additives and associated by-products commonly
associated with peptide synthesis. In order to monitor these products during a peptide synthesis
campaign, a quantitative detection method was developed, as detailed in Chapter 2. The intended
application of this method is for evaluation of all stages of peptide manufacture to ensure the removal
of these products, and therefore method validation is required to ensure the method can be accurately
used to provide precise results. Therefore this chapter presents the validation of a rapid liquid
chromatography method for the in-process determination of fourteen peptide coupling reagents used
in peptide synthesis. The analytes chosen were either used in the manufacture of some commercial
peptides or were under investigation for the manufacture of peptides in development. Analytical
method validation is achieved by performing testing on a number of validation characteristics such as
specificity, accuracy, linearity, precision, detection limit, quantitation limit and robustness, as per ICH
guidelines.
Note: The work described in this chapter can be broadly divided into three discrete sections.
Experimental work began with the optimised gradient discussed at the end of Chapter 2. Preliminary
investigation then revealed that buffer concentration had a significant effect upon the method
sensitivity for several analytes. The first section of this chapter therefore describes efforts to maximise
sensitivity by reducing buffer concentration in the mobile phase. Secondly, PyBrOP was removed
from the study due to its demonstrated poor performance as a peptide coupling reagent at Ipsen
Manufacturing Ireland LTD. This meant that the original gradient (initially 26 minutes long to
facilitate late elution of PyBrOP as shown in Figure 2.18 could be significantly reduced. Therefore,
the second section of this chapter describes re-optimisation of the original gradient to allow faster run
times, which includes studies into the effect of flow rate, buffer pH, etc., upon resolution. The final
section of this chapter deals with the validation of the method for all reagents under investigation
(without PyBrOP).
96
3.2 Experimental
3.2.1 Reagents and standards:
All reagents and standards were as described in Chapter 2.
3.2.2 Instrumentation
All instrumentation was as described in Chapter 2.
3.2.3 Effect of buffer concentration upon sensitivity
The evaluation of the detection limit of each reagent was carried out by dissolving each
reagent in ‗Sample set B‘ in the diluent at a concentration of 0.5 mg/mL. A 1/1000 dilution was
performed on each solution using diluent and each reagent was analysed on a 100 x 2.0 mm, YMC
Triart C18 1.9 μm column using ammonium formate buffers 5 mM, 10 mM and 15 mM (pH 4.2) with
acetonitrile as a mobile phase B. A multi-step gradient was employed as detailed in Table 3.1.
Table 3.1 Optimum gradient profile for buffer optimisation.
Time (min) Flow rate (mL/min) Mobile phase A Mobile phase B
Initial 0.275 97 % 3 %
9.00 0.275 97 % 3 %
9.01 0.3 97 % 3 %
12.00 0.3 92.5 % 7.5 %
12.01 0.4 87.5 % 12.5 %
16.00 0.4 60 % 40 %
22.00 0.4 97 % 3 %
23.00 0.4 97 % 3 %
26.00 0.275 97 % 3 % Note: This gradient program is the optimum program as determined in Chapter 2.
An injection volume of 10 μL was also employed for each injection. If no peak was present in
the 1/1000 dilution injection, a 1/500 dilution, or a 1/100 dilution was performed (if necessary) and
signal:noise ratios were calculated and compared.
3.2.4 Adjustment of mobile phase gradient following removal of PyBrOP
Following the removal of PyBrOP from the test mixture, the method gradient was re-
evaluated by analysing ‗Sample set B‘ (without PyBrOP) at a concentration of 0.5 mg/mL. The
gradients detailed in Table A21 to A30 in Appendix 1 incorporated the use of a YMC Triart C18 100
97
x 2.0 mm, 1.9 μm column and 5 mM ammonium formate pH 4.2 / acetonitrile as mobile phases. The
effect of flow rate (0.20 mL/min to 0.55 mL/min) upon the separation was also evaluated using the
optimum gradient.
3.2.5 Further evaluation of optimum buffer pH
Following the increase of Peptide 1 and Peptide 2 concentrations from 0.5 mg/mL during
method development (Chapter 2) to 5 mg/mL, the optimum pH range was re-evaluated for the
ammonium formate buffer at a range of 4.3 to 4.8. This was carried out by analysing a sample
containing Peptide 1 at a nominal concentration of 5 mg/mL and each of the peptide coupling
reagents, additives and by-products at their specification level of 0.1 % w/w. This was performed with
a range of ammonium formate pH values from 4.3 to 4.8 using the multi-step gradient detailed in
Table A30 in Appendix 1.
Note:
The analytical validation was performed using either a solution of Peptide 1 at nominal concentration
(5 mg/mL) as well as each of the analytes at a level of 0.1 mg/mL set (referred to hereafter as ‗Test
mix A‘) a or a solution of Peptide 2 at a nominal concentration (5 mg/mL) as well as each of the
analytes at a level of 0.1 mg/mL set (referred to hereafter as ‗Test mix B‘) a, unless otherwise stated.
The analysis was carried out using the multi-step gradient detailed in Table A30 in Appendix 1.
3.2.6 Specificity of the analytical method
The specificity of the analytical method was evaluated by preparing a solution ‗Test mix A‘
and ‗Test mix B‘. Each individual reagent, a mixture of both peptides with the reagents and a blank
injection of the diluent were injected individually using the optimised chromatographic conditions.
3.2.7 Accuracy of the analytical method
The accuracy of the method was evaluated at three different concentration levels in the range
of 80 – 120 % of ‗Test mix A‘. Each of the reagents was also individually diluted to a concentration
of 0.1 % w/w relative to 5 mg/mL and injected using the optimised chromatographic conditions.
3.2.8 Precision of the analytical method
System precision was evaluated from 6 injections of ‗Test mix A‘. Repeatability was
evaluated from 6 replicate preparations the above sample preparation. Intermediate precision was
evaluated from 6 replicate preparations of the above sample, which were analysed and evaluated
98
independently by two analysts, on different days, using different instrument set ups (difference
UHPLC instrument serial numbers and different mobile phase preparation).
3.2.9 Sensitivity of the analytical method
The limit of detection (LOD) of each of the analytes was evaluated by preparing a 0.1 mg/mL
solution and performing serial dilutions until a peak with a height of approximately 3 times the height
of the baseline was achieved. The limit of quantitation (LOQ) was evaluated by performing serial
dilutions of the above sample until a peak with a height of approximately 10 times the height of the
baseline was achieved.
3.2.10 Linearity of the analytical method
The evaluation of linearity of the detector response to each of the analytes involved injecting
each of the analytes from their limit of quantitation to 120 % of their specification of 0.1 % w/w. In
order to evaluate to relative response factor (RRF) of the analytes compared to the peptide products,
Peptide 1 and Peptide 2 were evaluated in the range of 50 % to 120 % of their nominal concentration
of 5 mg/mL.
3.2.11 Robustness of the analytical method
The robustness of the analytical method was evaluated from duplicate injections of ‗Test mix
A‘ on the method with small variations detailed as follows: buffer concentration (2.5 mM, 3.75 mM
and 7.5 mM), buffer pH (pH 4.5, 4.55 and 4.7), column temperature (20 °C and 30 °C), flow rate
(0.45 mL/min and 0.55 mL/min) and column to column variation (two YMC Triart C18 columns with
different serial numbers: 0210002430 and 0210002540).
3.2.12 Solution Stability
The stability of ‗Test mix A‘ was evaluated over a 135 hour period at ambient and
refrigerated storage conditions (2-8 °C) by injecting the test mix at specific timed intervals and
evaluating changes in peak area.
99
3.3 Results and discussion
3.3.1 Effect of buffer concentration upon sensitivity.
Usually, evaluation of method sensitivity is performed toward the end of a validation study,
and certainly after the optimum chromatographic conditions have been established (mobile phase
composition, gradient profiles etc.). However in this case, preliminary observations during method
development revealed that the concentration of buffer in mobile phase A (ammonium formate)
appeared to have a significant effect upon sensitivity for certain analytes, most notably DIC, DIU and
PyBrOP. Therefore it was considered prudent to more fully investigate the effect of buffer
concentration and then re-optimise chromatographic conditions as necessary as described in later
stages of this chapter.
A known impurity needs to be detected at levels of 0.1 % w/w and as a result, the minimum
requirement for limit of detection for each of the reagents is a 1/100 dilution of a 0.5 mg/mL solution,
relative to a 5 mg/mL peptide solution. Therefore, a 1/1000, 1/500 or a 1/100 dilution of a 0.5 mg/mL
solution of each analyte was made (equivalent to 0.01 % w/w, 0.02 % w/w or 0.1 % w/w respectively)
for this study.
The results of investigations into the effect of buffer concentration upon sensitivity are
displayed in Figure 3.1 below. For the most part, analyte concentrations were 0.01 % w/w unless
otherwise indicated in the figure caption. For most analytes, sensitivity was maximised with 5 mM
ammonium acetate relative to higher buffer concentrations with the exception of PyBOP (for which
15 mM was best) and HBTU, TCTU and TBTU (for which 10 mM was best). Additional studies into
the effect of detection wavelength were carried out since the original detection wavelength of 220 nm
had to be changed to 215 nm with the addition of DIC and DIU reagents to the study due to their poor
UV absorbance, (thereby further exacerbating the effect of buffer concentration on sensitivity at lower
wavelengths). Reducing the detection wavelength from 220 nm to 215 nm actually improved
sensitivity for most analytes: HOBt by 24 %, PyBrOP: 2,400 %, TMU: 65 %, DIC: 184 %, HCTU: 97
%, PyBOP: 10 %, DIU: 143 %, COMU: 100 %, HBTU: 67 % and TCTU: 43 %. There was an
observed reduction in sensitivity for other analytes; 6-ChloroHOBt: 26 %, HOAt: 60 %, PyClock: 58
%, Oxyma Pure: 19 % and TBTU: 29 %.
Nevertheless, a mobile phase buffer concentration of 5 mM, with a detection wavelength of
215 nm was selected as optimum conditions for further study since all analytes (including the initially
problematic DIC, DIU and PyBrOP) could be readily detected at 0.01 % w/w. Note: these preliminary
sensitivity studies were performed in strictly order to optimise chromatographic conditions, which
were further modified in the section which immediately follows. Therefore, a more rigorous
examination of method sensitivity is presented toward the end of this chapter, after all method
optimisation was completed.
100
Figure 3.1 Effect of buffer concentration upon signal:noise ratio for 0.01 % w/w injections of analyte.
Note: DIU was injected at 0.02 % w/w and DIC/PyBrOP were present at 0.1 % w/w.
3.3.2 Adjustment of mobile phase gradient following removal of PyBrOP
As can be seen from the final optimised chromatogram displayed at the end of Chapter 2,
PyBrOP exhibited significantly later retention relative to any of the other test analytes. This
necessitated an extended run time of 26 minutes to ensure that PyBrOP did not co-elute with the
peptide APIs. It was therefore fortuitous that Ipsen Manufacturing Ireland LTD., reported poor yield
results when PyBrOP was investigated as a peptide coupling reagent. This justified the removal of
PyBrOP from the set of analytes under investigation. As a result, there was a considerable scope to
significantly reduce the run time from 26 minutes by re-optimisation of the gradient (in terms of hold
times and acetonitrile concentrations). Resolution of the critical peak pair (HoAt and HBTU/TBTU),
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retention factor of the first peak, tailing and total run time were evaluated for gradients detailed in
Table A21 to A30 in Appendix 1, as detailed in Table 3.2.
Table 3.2 Results of gradient optimisation following the removal of PyBrOP from the mixture
Gradient
Rs. of critical
peak pair
k* of first
peak
Tailing -
largest result
Run time
(mins)
1 (A21) 1.79 2.1 1.8 26
2 (A22) 2.7 0.7 1.8 20
3 (A23) 2.9 2.1 1.7 18
4 (A24) 1.6 1.8 1.5 12
5 (A25) 1.23 1.8 1.4 14
6 (A26) 2.2 2.3 1.4 15
7 (A27) 1.6 2.5 1.3 16
8 (A28) 2.1 2.6 1.4 17
9 (A29) 2.9 2.2 1.5 15
10 (A30) 2.9 2.4 1.6 15
Table 3.2 demonstrates that the reduced run times typically resulted in slightly less peak
tailing. Gradient A30 in Appendix 1 was selected as optimum and for the sake of clarity, is presented
below in Table 3.3. The corresponding chromatogram is presented below as Figure (b) in Figure 3.2.
The total runtime (gradient time) of the method was reduced by 42 % (from 26 minutes to 15 minutes)
by the removal of PyBrOP from the test mix of analyse under investigation.
Table 3.3 Final optimised gradient after removal of PyBrOP from the test mix.
Time (mins) Flow rate (mL/min) Mobile phase A (%) Mobile phase B (%)
0.00 0.50 97 3
4.00 0.50 97 3
10.00 0.50 92.5 7.5
10.25 0.50 87.5 12.5
11.50 0.50 87.5 12.5
12.00 0.50 60 40
12.50 0.50 97 3
15 0.50 97 3
Gradient optimisation also necessitated an examination of the effect of flow rate upon the
separation and resulted are illustrated in Figure 3.2. Specifically, using the optimised gradient, flow
rates of 0.2 mL/min to 0.55 mL/min were applied, with lower flow rates (0.2 mL/min, 0.3 mL/min
and 0.4 mL/min) resulting in co-elution of early peaks (HOAt and TBTU/HBTU). This is due to
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increased retention of peaks at reduced flow rates since the analytes are travelling through the column
at a slower pace leading to chromatographic zone broadening and co-elution of closely eluting peaks.
The reason for the chromatographic zone broadening is due to unwanted longitudinal diffusion of
bands at lower (i.e. non-optimum) flow rates.
Figure 3.2 Effect of flow rate upon separation. (a): 0.55 mL/min, (b): 0.50 mL/min, (c): 0.40 mL/min,
(d): 0.30 mL/min, (e): 0.20 mL/min. Chromatographic conditions: Column: 100 x 2.0 mm, YMC
Triart C18, 1.9 μm dp, Mobile phase A: 5 mM ammonium formate pH 4.2, Mobile phase B:
acetonitrile, Gradient program: Table 3.3, Injection volume: 5 µL, Column temperature: 25 oC,
Detection wavelength: 215 nm. Note: DIC is a co-eluting peak with DIU.
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Lower flow rates also resulted in the unacceptably late elution of more strongly retained
analytes (6-ChloroHOBt/Pyclock, Oxyma Pure, DIU/DIC), which in extreme cases lead to their co-
elution with the main peptide API peak (chromatograms c, d and e in Figure 3.2). An optimum flow
rate of 0.50 mL/min was therefore chosen which is illustrated as chromatogram (b) in Figure 3.2,
based upon the optimised resolution between HOAt and TBTU/HBTU.
3.3.3 Further evaluation of optimum buffer pH
Peptide 1 and Peptide 2 were evaluated at a concentration of 0.5 mg/mL during method development
in Chapter 2, however in order to maximise the quantitation limit for the analytes of interest, the
concentration of Peptide 1 and Peptide 2 was increased to 5 mg/mL. Interestingly, this resulted in a
decrease in retention for most analytes; 1.2 % for Oxyma Pure, 5.2 % for DIU/DIC, 7.2 % for COMU,
4.8 % for TMU, 6.2 % for HCTU/TCTU and 1.2 % for HOBt/PyBOP. However, the resolution
between the critical peak pair (HOAt and TBTU/HBTU) was significantly affected since the reduction
in retention time for both peaks was unequal. Specifically, the retention of HOAt decreased by only
3.9 % whereas the retention of TBTU/HBTU decreased by 8.2 % resulting in a loss of resolution
between this critical peak pair as shown in Figure 3.3 below. This reduction in retention times
occurred due to overloading of the stationary phase with the peptide API.
Figure 3.3 Effect of Peptide 1 concentration upon analyte retention. (a) Mix of reagents with Peptide
1 at 0.5 mg/mL (b) Mix of reagents with Peptide 1 at 5 mg/mL. Chromatographic conditions as in
Figure 3.2. Mobile phase flow rate: 0.5 mL/min. Note: DIC is a co-eluting peak with DIU.
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Previous mobile phase pH studies in Chapter 2 indicated that changes in mobile phase pH
resulted in selectivity changes for early eluting peaks and so mobile phase pH evaluation was re-
visited here. Mobile phase pH was adjusted between pH 4.3 and 4.8 as illustrated in Figure 3.4.
Figure 3.4 Effect of pH on analyte retention. Chromatographic conditions as per Figure 3.3.
As can be seen, the critical peak pair at pH 4.3 was HOAt and TBTU/HBTU but
with inadequate resolution of < 1.5. Increasing mobile phase pH resulted in a greater decrease in
retention of HOAt relative to TBTU/HBTU such that resolution improved correspondingly.
Interestingly, increases in mobile phase pH also lead to significant changes in selectivity for the
Oxyma Pure and the DIU/DIC peak such that their elution order actually switched at 4.4 – 4.5. This
resulted in the emergence of a new critical peak pair in this pH region. Therefore, a mobile phase pH
of 4.6 was chosen as optimum resulting in resolution (resolution = 2.3) for the HOAt and
TBTU/HBTU peak pair, and (resolution = 3.8) for the Oxyma Pure and DIU/DIC peak pair. The final
optimised chromatogram is shown in Figure 3.5 using a mobile phase pH of 4.6. All validation
parameters, with the exception of robustness, were evaluated using the chromatographic conditions
shown in the caption of Figure 3.5. An injection volume of 5 µL was chosen as the injection volume
in order to minimise peak shape distortion for early eluting peaks.
105
Figure 3.5 Final optimised separation of fourteen peptide coupling reagents from a selected commercial peptide API. Chromatographic conditions: Column:
100 x 2.0 mm, YMC Triart C18, 1.9 μm dp, Mobile phase A: 5 mM ammonium formate pH 4.6, Mobile phase B: acetonitrile, Gradient program: Table 3.3,
Flow rate 0.5 mL/min, Injection volume: 5 µL, Column temperature: 25 oC, Detection wavelength: 215 nm
.
106
3.3.4 Validation of analytical method for the determination of peptide coupling
reagents, additives and associated by-products
The International Conference on Harmonisation (ICH) of technical requirements for
registration of pharmaceuticals for human use outlines that a registration application should include
documented evidence that the analytical procedures are validated and suitable for the detection and
quantification of impurities [115]. The validation of an analytical procedure is to demonstrate that it is
suitable for its intended purpose and the ICH has introduced a guideline on how this should be
performed [116]. This guideline outlines that the number of validation characteristics that should be
considered, depending on the type of method being validated [116]. Analytical methods for testing
impurities can be either a quantitative test or a limit test and different validation characteristics are
required for a quantitative test relative to a limit test [116]. These validation characteristics include
accuracy, precision, repeatability, intermediate precision, specificity, detection and quantitation limit,
linearity and range [116].
3.3.4.1 Method validation background
Peptide coupling reagents and by-products are monitored in peptide manufacturing campaigns
for development batches and testing of these reagents is also required for the assignation of primary
reference standards in two commercial APIs. There is no specification for the peptide coupling
reagents and associated by-products in campaigns for clinical batches because the specification is
dosage dependent. The specification for peptide coupling reagents and by-products is 0.1% (w/w) for
the assignation of a primary reference standard for the two commercial peptide APIs. As a result, the
nominal specification was set at 0.1% (w/w) in this validation and this is the specification requirement
for known impurities.
The validation was performed on two Ipsen peptides (referred to as ―Peptide 1‖ and ―Peptide
2‖) spiked with reagents. Both peptides were evaluated in the selectivity and linearity sections (which
follow hereafter) to demonstrate specificity and to calculate RRF values relative to each peptide,
however only Peptide 1 was evaluated in remaining validation parameters.
3.3.5 Specificity of the analytical method
Specificity of an analytical method is the ability to measure an analyte in the presence of
interference, such as synthetic precursors, excipients, enantiomers and known degradation products
that may be expected to be present in the sample matrix [116]. For chromatographic methods,
representative chromatograms demonstrating the discrimination of the peptides from the peptide
coupling reagents, additives and associated by-products demonstrates specificity of the analytical
method [116]. The specificity acceptance criteria, which states the peak tailing of each peak should be
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≤ 2.0, the retention factor (k*) should be ≥ 1.0 and the resolution of all peaks should be ≥ 1.5, were
fulfilled and the blank chromatogram was free from interfering peaks, as illustrated in Figure 3.6. The
method was determined to be selective with respect to the detection of each of the peptide coupling
reagents, additives and by-products in the presence of both Peptide 1 and Peptide 2, as demonstrated
in Figure 3.7 and 3.8.
Figure 3.6 Blank chromatogram demonstrating no interfering peaks present. Chromatographic
conditions as shown in Figure 3.5.
Figure 3.7 Chromatogram demonstrating specificity of reagents in the presence of Peptide 1.
Chromatographic conditions as shown in Figure 3.5. Note: Peptide 1 is labelled as “BIM-23014C”.
108
Figure 3.8 Chromatogram demonstrating specificity of reagents in the presence of Peptide 2.
Chromatographic conditions as shown in Figure 3.5. Note: Peptide 2 is labelled as “BIM-21003C”.
3.3.6 Accuracy of the analytical method
The accuracy of an analytical procedure demonstrates the closeness of agreement between the
result that is accepted, either as a conventional true result or an accepted reference result, and the
result determined [116]. Accuracy is typically demonstrated as percentage recovery where the analyte
is spiked into a sample and also individually analysed to determine the effect the sample has on the
analyte [114]. The accuracy of each of the reagents was assessed on duplicate preparations of the
reagents spiked into Peptide 1 over three ranges. The reagents were also analysed in the absence of
Peptide 1 and the results were compared to determine the percentage recovery relative to peak area.
All reagents, with the exception of PyClocK, were demonstrated to be accurate within the range of
90.0 % to 107.0 % as shown below in Table 3.4. The method was determined to be inaccurate with
respect to PyClocK.
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Table 3.4 Accuracy of each analyte at 80 %, 100 % and 120 % of the specified range
Accuracy range 80 % 100 % 120 %
TMU recovery 104.5 % 106.2 % 106.0 %
TBTU recovery 97.0 % 99.9 % 100.0 %
HOBt recovery 100.9 % 102.6 % 102.9 %
TCTU recovery 102.0 % 102.1 % 99.2 %
Oxyma Pure recovery 100.2 % 100.8 % 100.4 %
DIC recovery 103.6 % 106.3 % 103.1 %
6-ChloroHOBt recovery 106.0 % 104.9 % 105.0 %
HOAt recovery 98.4 % 99.1 % 98.2 %
HBTU recovery 103.1 % 103.4 % 102.7 %
PyBOP recovery 98.5 % 102.0 % 105.6 %
HCTU recovery 100.9 % 100.3 % 99.2 %
COMU recovery 100.8 % 103.1 % 101.1 %
DIU recovery 93.0 % 91.9 % 90.6 %
PyClocK recovery 24.5 % 28.0 % 37.0 %
3.3.7 Precision of the analytical method
The precision of an analytical procedure expresses the closeness of agreement between a
series of measurements obtained from multiple sampling performed on the same sample under the
same conditions [116]. Precision may be considered at three levels: repeatability, intermediate
precision and reproducibility and is usually expressed as the variance, standard deviation or
coefficient of variation of a series of measurements [116]. Repeatability expresses the precision under
the same operating conditions over a short interval of time [116]. It is also known as intra-precision
and can be assessed using 9 determinations covering a specified range or 6 determinations of the 100
% range [114]. The method was demonstrated to be repeatable with the results for all the reagents
within the criteria of ≤ 5.3 % RSD of peak area (Ipsen Manufacturing Ireland LTD. internal
specification), as detailed in Table 3.5. Some of the reagents demonstrated a higher % RSD than
others and this is due to the stability of the reagents as detailed in Section 3 3.5. Retention time
precision was also evaluated for replicate injections of a test mix and found to be ≤ 0.52 % for all
analytes.
Intermediate precision expresses within-laboratories variations, such as different days,
different analysts and different equipment. The criteria of % RSD of ≤ 5.3 % of peak area was met for
all peptide coupling reagents, additive and associated by-products and therefore the method was
determined to be precise with respect to variation within the same laboratory. System precision was
also assessed to determine the impact of the system on the same sample. The criteria of % RSD of ≤
5.3 % for peak area was also met for all peptide coupling reagents, additive and associated by-
products, as detailed in Table 3.5.
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Table 3.5 Precision, repeatability and intermediate precision results
Reagent
Precision
% RSD
Precision
(Retention time)
% RSD
Repeatability
% RSD
Int. precision
% RSD
HOAt 0.4% 0.38% 0.4% 2.3%
TBTU/HBTU 1.4% 0.52% 1.3% 1.5%
HOBt/PyBOP 0.7% 0.23% 0.5% 1.9%
HCTU/TCTU 1.2% 0.38% 1.9% 3.0%
TMU 1.2% 0.22% 0.9% 2.2%
COMU 1.7% 0.23% 1.5% 1.8%
Oxyma Pure 1.4% 0.17% 2.3% 4.5%
DIU/DIC 2.2% 0.20% 5.2% 4.9%
6-Chloro/PyClocK 1.2% 0.08% 2.4% 3.5% Note: Precision was determined by evaluating peak area, except where indicated above.
3.3.8 Limit of Quantitation (LOQ) of the analytical method
The limit of quantitation is the lowest amount of analyte in the sample that can be
quantitatively determined with suitable precision and accuracy [114,116]. The LOQ was determined
using a signal to noise approach where the LOQ was determined as the concentration that results in a
signal to noise of 10 to 1. The quantitation limit is affected by the accuracy of the sample preparation
and also the detector sensitivity at such a low concentration [114]. The LOQ value for each of the
peptide coupling reagents, additives and associated by-products is detailed in Table 3.6.
Table 3.6 Limit of quantitation results
Reagent LOQ (% w/w) LOQ % RSD
HOAt 0.0013 7.5%
TBTU 0.0080 3.6%
HBTU 0.0010 7.7%
HOBt 0.0007 15.8%
PyBOP 0.0400 8.7%
HCTU 0.0080 16.0%
TCTU 0.0080 8.8%
TMU 0.0010 19.0%
COMU 0.0066 6.3%
Oxyma Pure 0.0080 10.2%
DIU 0.0266 16.7%
6-Chloro 0.0050 15.2%
PyClocK 0.0067 15.5%
DIC 0.0500 18.9%
There are significant differences in some of the LOQ values and this is related to the
maximum absorbance at the detection wavelength of 215 nm. HOAt demonstrates a very low LOQ of
0.000667 % w/w and this is a reflection on the high UV absorbance at 215 nm as demonstrated in
Figure 2.3, whereas DIU has a higher LOQ at 0.0133 % which reflects the low UV absorbance at 215
111
nm as demonstrated in Figure 2.16. To ensure that the LOQ results are reproducible, six injections of
the LOQ concentration of each of the reagents were evaluated. All % RSD results were within the
criteria of ≤ 20.0 % RSD for peak area, as detailed in Table 3.6 (Ipsen Manufacturing Ireland LTD.
Internal specification).
3.3.9 Limit of Detection (LOD) of the analytical method
The detection limit of an analytical procedure is the lowest amount of analyte in a sample that
can be detected but not quantitated as an exact value [116]. The detection limit is determined as the
concentration amount that results in a peak with a height at least 3 times as high as the baseline noise
level measured [116]. The LOD results are not required to be repeatable as the analytes will not be
quantified at this concentration. However, LOD reproducibility was assessed as part of the validation
for information purposes on six injections of the LOD concentration of each of the reagents. All %
RSD results were within the LOQ criteria of ≤ 20.0 % RSD for peak area, as detailed in Table 3.7.
Table 3.7 Limit of detection results
Reagent LOD (% w/w) LOD % RSD
HOAt 0.0007 5.2%
TBTU 0.0040 3.9%
HBTU 0.0005 5.9%
HOBt 0.0003 9.8%
PyBOP 0.0100 8.4%
HCTU 0.0040 4.0%
TCTU 0.0040 7.9%
TMU 0.0005 9.7%
COMU 0.0040 6.9%
Oxyma Pure 0.0040 5.2%
DIU 0.0133 16.5%
6-Chloro 0.0010 10.2%
PyClock 0.0133 4.8%
DIC 0.0250 8.5%
3.3.10 Linearity of the analytical method
The linearity is the ability of the analytical procedure to produce test results which are directly
proportional to the concentration range of the analyte in samples within a given range [116]. For all
peptide synthesis and degradation products, the linearity was assessed in a range from LOQ to 120 %
of the expected specification of 0.1 % w/w, relative to a concentration of 5 mg/mL. The linearity of
the Peptide 1 and Peptide 2 was assessed at 50 to 120 % of the peptide concentration of 5 mg/mL. A
plot of peak area versus concentration was compiled to demonstrate linearity for each of the reagents
and each of the peptides. Table 3.8 details the slope and residual sum of squares. All peptide coupling
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reagents, additives and associated by-products meet the criteria of residual sum of squares ≥ 0.99.
Peptide 1 and Peptide 2 also meet their linearity criteria of ≥ 0.999.
Table 3.8 Linearity of analytical method
Reagent Linearity range Slope Residual sum
of squares
HOAt 0.000667 % - 0.12 % 67994387.827 1.00
TBTU 0.004 %- 0.12 % 22008078.925 1.00
HBTU 0.0005 % - 0.12 % 19320030.453 1.00
HOBt 0.000334 % - 0.12 % 87581346.212 1.00
PyBOP 0.01 % - 0.12 % 6322842.105 1.00
HCTU 0.004 % - 0.12 % 35646533.957 1.00
TCTU 0.004 % - 0.12 % 42421895.957 1.00
TMU 0.0005 % - 0.12 % 34269185.825 1.00
COMU 0.004 % - 0.12 % 10892203.050 1.00
Oxyma Pure 0.004 % - 0.12 % 16025780.438 1.00
DIU 0.0133 % - 0.12 % 1942903.897 0.99
6-ChloroHOBt 0.001 % - 0.12 % 82702151.435 1.00
PyClocK 0.0133 % - 0.12 % 5876492.443 1.00
DIC 0.025 - 0.12 % 1560661.017 0.99
Peptide 1 50 to 120 % 5429795.322 0.999
Peptide 2 50 to 120 % 10264856.210 0.999
The relative response factor can be used to correct differences in response between any
related substances such as the reagents and the drug substance [114]. The relative response factor is
determined by comparing the slope of the related substance to the slope of the drug substance [114]. If
a relative response factor is significantly different, such as a difference of 20 %, a correction factor
should be applied to the calculation of the concentration of the related substance in the drug substance
[114]. If this correction factor is not applied then the results can be grossly overestimated or
underestimated [114]. Table 3.9 details the results for the relative response factor results. The relative
was determined using the slope of the linearity curve according to the formula - RRF=slope impurity /
slope API. In order to account for the relative response factor, the result for the reagent present in the
Peptide sample must be multiplied by 1/RRF value.
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Table 3.9 Determination of relative response factors
Reagent Slope Peptide 1
Slope
RRF Peptide
1
Peptide 2
Slope
RRF Peptide
2
HOAt 67994387.827 5576075.550 12.19 25507694.000 2.67
TBTU 22008078.925 5576075.550 3.95 10264856.210 2.14
HBTU 19320030.453 5576075.550 3.46 10264856.210 1.88
HOBt 87581346.212 5576075.550 15.71 10264856.210 8.53
PyBOP 6322842.105 5576075.550 1.13 10264856.210 0.62
HCTU 35646533.957 5576075.550 6.39 10264856.210 3.47
TCTU 42421895.957 5576075.550 7.61 10264856.210 4.13
TMU 34269185.825 5576075.550 6.15 10264856.210 3.34
COMU 10892203.050 5576075.550 1.95 10264856.210 1.06
Oxyma Pure 16025780.438 5576075.550 2.87 10264856.210 1.56
DIU 1942903.897 5576075.550 0.35 10264856.210 0.19
6-ChloroHOBt 82702151.435 5576075.550 14.83 10264856.210 8.06
PyClock 5876492.443 5576075.550 1.05 10264856.210 0.57
DIC 1560661.017 5576075.550 0.28 10264856.210 0.15
3.3.11 Robustness of the analytical method
The robustness of an analytical procedure is a measure of its ability to remain unaffected by
small, but deliberate changes in method parameters and provides an indication of its reliability of the
analytical method during normal usage [116]. Robustness was assessed on critical parameters of the
analytical method such as column variation, column temperature, buffer concentration and pH and
also flow rate. The criteria for method robustness states the peak tailing of each peak should be ≤ 2.0,
the retention factor (k*) should be ≥ 1.0 and the resolution of all peaks should be ≥ 1.5. Figure 3.9
demonstrates that the method was robust with respect to column to column variation. Columns with
different serial numbers were evaluated and all criteria were achieved on both columns. This is the
most important robustness parameter as a method must be robust to change in columns as this
regularly occurs when a method is in routine use.
114
Figure 3.9: Robustness testing on YMC Triart columns with different serial numbers – (a) Column
serial number 0210002430 and (b) Column serial number 0210002540. Chromatographic conditions
as shown in Figure 3.5.
Figure 3.10 demonstrates the robustness of the method to changes in flow rate. The flow rate
was assessed at ± 0.05 mL/min and all criteria were achieved at each flow rate. Peak broadening was
observed for the 6-ChloroHOBt/PyClocK peak for the higher flow rate of 0.55 mL/min, however all
chromatographic performance criteria were achieved. The flow rate is dictated by the UHPLC
instrument and it is unlikely that the flow rate will be impacted by as much as ± 0.05 mL/min,
however if this did occur, the analytical method is capable of producing reproducible results.
115
Figure 3.10: Robustness testing for flow rate variation – (a) flow rate: 0.45 mL/min, (b) flow rate:
0.50 mL/min and (c) flow rate: 0.55 mL/min. Chromatographic conditions as shown in Figure 3.5.
Figure 3.11 shows the effect of column temperature on the analytical method. The method
was assessed using column temperatures of 20 °C, 25 °C (normal conditions) and 30 °C and all
chromatographic performance criteria were achieved for each condition. The reduction in column
temperature resulted in the critical peak pair of Oxyma Pure and DIU/DIC to elute closer together
(resolution = 2.33) and an increase in column temperature has the opposite effect (resolution = 6.12).
Peak broadening was also observed for the 6-ChloroHOBt/PyClocK peak at the higher column
temperature of 30 °C, however all chromatographic performance criteria were achieved.
116
Figure 3.11: Robustness testing for column column temperature variation - (a) column temperature:
20 °C, (b) column temperature: 25 °C and (c) column temperature: 30 °C. Chromatographic
conditions as shown in Figure 3.5.
Figure 3.12 shows the effect of buffer concentration on the analytical method. The method
was initially assessed using an ammonium formate concentration of 2.5 mM, 5 mM (normal
conditions) and 7.5 mM. The reduction in ammonium formate concentration to 2.5 mM resulted in the
critical peak pair of Oxyma Pure and DIU/DIC and HOAt and TBTU/HBTU eluting closer together
and the results failed the criteria for resolution ≥ 1.5. As a result, an additional concentration of 3.75
mM ammonium formate was added to the robustness evaluation. All criteria were achieved for 3.75
mM and 7.5 mM ammonium formate. As the method is not robust at a low concentration of 2.5 mM
ammonium formate, the concentration of the ammonium formate needs to be suitably controlled and a
precautionary statement should be included in the method. The buffer concentration effected retention
times because the retention of ionisable analytes in this instance is likely governed by a range of
different retention mechanisms such as ion exchange interactions with deprotonated silonols on the
silica support particle, as well as hydrophobic interactions with the C18 ligand. The buffer acts as a
117
counter ion to compete with negatively charged silanols which is a phenomenon not typically
observed for neutral analytes.
Figure 3.12: Robustness testing for buffer concentration variation. (a) 2.5 mM ammonium formate,
(b) 3.75 mM ammonium formate, (c) 5 mM ammonium formate and (d) 7.5 mM ammonium formate.
Chromatographic conditions as shown in Figure 3.5.
Figure 3.13 demonstrates the effect of buffer pH on the analytical method. The method was
initially assessed using ammonium formate pH of 4.5, 4.6 (normal conditions) and 4.7.
118
Figure 3.13: Robustness testing for variation of buffer pH. (a): pH 4.5, (b): pH 4.55, (c): pH 4.6 and
(d): pH 4.7. Chromatographic conditions as shown in Figure 3.5.
The reduction in ammonium formate pH to 4.5 resulted in the critical peak pair of Oxyma
Pure and DIU/DIC to elute closer together and the results failed the criteria for resolution ≥ 1.5. As a
result, an additional pH of 4.55 was added to the robustness evaluation. All criteria were achieved for
pH 4.55 and 4.7 despite a deterioration of peak shape for 6-ChloroHOBt/PyClock at the higher pH. As
the method is not robust at a low pH of 4.5, the pH of the ammonium formate also needs to be
suitably controlled and a precautionary statement should be included in the method.
119
3.3.12 Solution stability
In relation to the detection method, the aim is to accurately determine the concentration of
peptide coupling reagents, additives and associated by-products in API. As this API is formulated as a
drug substance it is important to access the effect of the final concentration of these reagents if left in
solution over time. As a result, the API should be assessed for reagents initially after sample make up
and also after approximately 72 hours. This will insure the reagents that increase in area count due to
degradation of other reagents do not go above the threshold of toxicological concern in the final
peptide. Solution stability is usually evaluated by comparison of freshly prepared solutions with those
stored at particular conditions for a specific length of time. Therefore, a mixture containing Peptide 1
at a nominal concentration of 5 mg/mL and each of the peptide coupling reagents, additives and by-
products at their specification level of 0.1 % w/w was evaluated over a 135 hour period at ambient
and refrigerated storage conditions (2-8 ºC). For this study, a change in peak area ≤ 5.3 % was
considered to be indicative of solute stability.
Firstly, Figure 3.14 and Figure 3.15 both illustrate the stability of each of the reagents at
ambient temperature over the evaluation period (with some of the analytes normalized to begin at 100
% for illustrative purposes). HOAt was determined to be stable for approximate 20 hours at ambient
temperature, with a % change in peak area of 5.03 %, whereas COMU was stable for up to 16 hours.
Conversely, all other solutes were stable for 1 hour or less, with the degradation of TBTU/HBTU and
TCTU/HCTU particularly notable over the 135 hour time period as shown in Figure 3.13. As a result
of the degradation of these analytes, the peak area of HOBt/PyBOP, TMU, and 6-
ChloroHOBT/PyClocK all correspondingly increased significantly within 0.5 hours since
TBTU/HBTU and TCTU/HCTU were demonstrated to degrade to these more stable forms as
discussed in Chapter 2.
Figure 3.14: Stability at ambient sample temperature for selected analytes.
120
Figure 3.15: Stability at ambient sample temperature for remaining analytes in the study.
Figure 3.16 shows a chromatogram comparison for the test mix injected immediately after
preparation, and also after 135 hours when stored in the HPLC auto sampler at ambient temperature.
For illustrative purposes, arrows are included in the figure to indicate which analytes increase or
decrease in peak area over the time period, and this can readily be cross-referenced with the patterns
shown in Figure 3.14 and Figure 3.15.
Figure 3.16: Test mix stability at ambient sample temperature over 135 hours. (a) time-point: 0 hours
(b) time-point: 135 hours. Chromatographic conditions as shown in Figure 3.5.
121
As a result of the poor solute stability when test solutions were stored in the auto-sampler at
ambient temperature, a second study was performed in which solutions were held at 5 oC and injected
at timed intervals. Figure 3.17 and Figure 3.18 clearly illustrate that solution stability (as indicted by a
change in peak area of not more than 5.5 %) significantly increased for all analytes with the exception
of 6-ChloroHOBt/PyClock for which there was no improvement. The largest improvement in solute
stability was observed for DIU/DIC which increased by a factor for 40 when stored at 5 oC rather than
ambient temperatures, followed by TBTU/HBTU and HOAt which both increased by a factor of
seven. Although all reagents did appear to degrade over time, even when stored at 5 oC in the auto
sampler, nevertheless the degradation was significantly reduced, clearly demonstrating a distinct
advantage of the use of an auto-sampler cooling function during HPLC analysis.
Figure 3.17: Comparison of solute stability (≤ 5.3 % change in peak area) at ambient temperature
and 5 oC for selected reagents.
122
Figure 3.18: Comparison of solute stability (≤ 5.3 % change in peak area) at ambient temperature
and 5 oC for the remaining reagents in this study.
3.4 Conclusions
A fast, reliable ultra-high performance liquid chromatography method for the simultaneous
determination of peptide coupling reagents, additives and by-products used in peptide synthesis, was
developed an d validated. Using a YMC Triart reverse-phase UHPLC column with particle size of
1.9 µm, the UV assay can detect 14 commonly used peptide synthesis reagents in the presence of 2
peptides within a run time of 15 minutes. This 15 minute method was determined to be selective and
capable of accurately quantitating the amount of TMU, HOBt, HCTU, HBTU, 6-ChloroHOBt, TBTU,
Oxyma Pure, COMU, DIU, DIC, PyBOP, and TCTU in the presence of two peptides from Ipsen
Manufacturing Ireland LTD. The precise method was determined to be linear for the response of each
reagent and both peptides. The method was proven to be robust with respect to variations in the
method parameters and it is also capable of reproducibly detecting levels below the required
threshold. This rapid UHPLC method is directly transferable onto LC-MS and offers significant
advantages over current HPLC methods with long run times and methods that can only detect single
analytes.
123
_________________________________________________________________________
Chapter 4
Conclusion
__________________________________________________________________________
4.
124
4.1 Overall conclusion
In conclusion, a 15 minute ultra-high performance liquid chromatography method for the
simultaneous determination of fourteen peptide coupling reagents, additives and by-products used in
peptide synthesis, was developed using a YMC Triart reverse-phase UHPLC column with particle
size of 1.9 µm with UV detection. The method development involved evaluation of 17 commercially
available stationary phase and 12 mobile phase systems. This method was subsequently validated
according to ICH guidelines and it was determined to be selective of accurately quantitating the
amount of TMU, HOBt, HCTU, HBTU, 6-ChloroHOBt, TBTU, Oxyma Pure, COMU, DIU, DIC,
PyBOP, and TCTU in the presence of two peptides from Ipsen Manufacturing Ireland LTD. The
method was also determined to be valid for linearity, precision and robustness with an acceptable
limit of detection and limit of quantitation value for each reagent.
The determination of peptide coupling reagents, additives and associated by-products is
important during peptide synthesis to ensure the concentration of these products are below the
threshold of toxicological concern in the final peptide. This method was required because studies at
Ipsen Manufacturing Ireland LTD. have revealed that some peptide coupling reagents may in fact not
be fully removed from the peptide product during peptide manufacture. The analytes evaluated were
either used in the manufacture of some commercial peptides or were under investigation for the
manufacture of peptides in development in Ipsen Manufacturing Ireland LTD. This rapid assay
replaces multiple HPLC methods of run time greater than 60 minutes for the in-process testing during
peptide synthesis and it also has applicability as a release test for the final API. To the best of my
knowledge, no chromatographic separation has been developed for all of the reagents evaluated in the
scope of this study.
The rapid UHPLC method is directly transferable onto LC-MS and offers significant
advantages over current HPLC methods with long run times and methods that can only detect single
analytes. It is anticipated that this method will be used in the biopharmaceutical industry, particularly
in Ipsen Manufacturing Ireland LTD.
125
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132
APPENDIX 1 –METHOD DEVELOPMENT: GRADIENT PROFILES
133
134
135
APPENDIX 2 – FINAL METHOD OPTIMISATION: GRADIENT PROFILES
136
APPENDIX 3 –METHOD OPTIMISATION: RESULTS TABLES
Table 1 Effect of buffer pH upon chromatographic performance for Sample Set B.
pH
Resolution of critical
peak pair
Plate count -
smallest result
k* of first
peak
Tailing -
largest result
2.8 1.6 2,152 2.6 2.2
2.9 1.6 2,544 2.5 1.7
3.0 1.6 2,380 2.5 1.9
3.1 1.7 2,387 2.4 1.7
3.2 1.9 2,547 2.4 1.5
3.3 1.3* 829 2.4 1.5
3.8 Not calculated** Not calculated* 2.4 1.9
4.3 2.6 707 1.6 1.8
4.8 2.5 102 1.2 4.6
*Change in critical peak pair
**Empower software did not automatically calculate result due to interference with a closely eluting peak
Table 2 Effect of flow rate on chromatographic performance for Sample set B
Flow rate
Resolution of
critical peak pair
Plate count -
smallest result
k* of first
peak
Tailing -
largest result
0.25 mL/min Not calculated* 3,522 3.3 1.5
0.30 mL/min 1.7 3,147 2.3 1.9
0.35 mL/min 1.9 2,699 2.1 1.5
*Empower software did not automatically calculate result due to interference with a closely eluting peak
Table 3 Effect of column temperature upon chromatographic performance for Sample set B
Temperature
Resolution of
critical peak pair
Plate count -
smallest result
k* of first
peak
Tailing -
largest result
10 ◦C Not calculated* 3,148 2.9 1.5
15 ◦C 1.7 3,145 2.7 1.8
20 ◦C 1.7 3,077 2.6 1.6
25 ◦C 1.6 3,023 2.5 1.5
30 ◦C Not calculated* 2,800 2.4 1.6
35 ◦C Not calculated* 2,509 2.2 1.5
40 ◦C Not calculated* 2,288 2.1 1.5
45 ◦C Not calculated* 1,991 2.0 1.5
137
*Empower software did not automatically calculate result due to interference with a closely eluting peak
Table 4 Effect of acetonitrile concentration upon retention of PyBrOP.
% Acetonitrile / time PyBrOP Rt PyBrOP tailing
30 % within 20 minutes 21.868 2.0
40 % within 20 minutes 21.311 1.3
50 % within 20 minutes 20.732 1.3
Table 5 Effect of pH upon chromatographic performance and AU response for Sample set B
pH
Resolution of
critical peak
pair
Plate count -
smallest result
k* of first
peak
Response
AU of
largest peak
Tailing -
largest
result
3.2 1.0 1,084 3.5 1.1 1.6
3.3 1.0 1,125 3.5 1.3 1.7
3.4 1.2 1,274 3.5 1.8 2.1
3.6 1.4 2,465 3.5 2.1 2.0
3.8 Not calculated* Not calculated* 3.3 2.5 2.0
3,9 Not calculated* 1,777 3.1 2.5 2.0
4.2 2.5 1,370 1.7 2.5 2.0
4.4 1.9 1,381 2.1 2.5 2.0
4.6 Not calculated* 1,172 2.0 2.5 2.0
4.8 Not calculated* 768 1.8 2.5 2.1
*Empower software did not automatically calculate result due to interference with a closely eluting peak
Table 6 Results from optimum buffer concentration for separation
Conc.
Resolution of
critical peak
pair
Plate count -
smallest
result
k* of first
peak
Response AU
of largest peak
Tailing -
largest result
5 mM 0.4 3,593 3.3 2.4 2.0
10 mM 1.0 1,810 3.5 2.0 2.3
15 mM 0.8 2,235 3.6 1.2 1.9
20 mM 1.3 2,297 3.6 1.0 2.2
25 mM 2.0 2,298 3.7 0.6 2.1
30 mM 2.5 2,254 3.8 0.5 2.0
40 mM 2.4 2,151 3.8 0.2 1.9
138
Table 7 Results of gradient evaluation
Gradien
t
Rs. of
critical
peak pair
Plate count -
smallest result
k of first
peak
Response AU
of largest peak
Tailing -
largest
result
1 0.9 1,403 3.0 2.5 2.2
2 1.1 1,302 2.8 2.5 2.1
3 1.4 1,140 2.2 2.5 2.1
4 1.2 1,885 3.0 2.5 2.1
5 1.1 1,883 3.1 2.5 2.1
6 1.3 1,306 2.8 2.5 2.1
7 1.7 1,299 2.4 2.5 2.0
8 2.0 1,225 2.4 2.5 2.1
9 2.0 1,504 2.5 2.5 2.1
10 2.1 1,427 2.5 2.5 2.0
11 2.7* 1,584 2.6 2.5 1.6
12 2.9 1,530 2.5 2.5 1.6
Note: Gradient profiles detailed on page 10. *Change in critical peak pair
